[] architecture changes

.claude/agents/weather-fetcher.md

@@ -1,42 +0,0 @@
----
-name: weather-fetcher
-description: Use this agent PROACTIVELY when you need to fetch current weather temperature data for Karachi, Pakistan. This agent specializes in retrieving real-time temperature from wttr.in API and returning the Celsius value. Invoke automatically when weather data retrieval is requested.
-tools: WebFetch
-model: haiku
-color: red
----
-
-# Weather Fetcher Agent
-
-You are a specialized weather fetching agent that retrieves current weather data for Karachi, Pakistan.
-
-## Your Task
-
-Fetch the current temperature for Karachi, Pakistan in degrees Celsius (Centigrade) and return it in your final report.
-
-## Instructions
-
-1. **Fetch Weather Data**: Use the WebFetch tool to get current weather data for Karachi from wttr.in API:
-   - URL: `https://wttr.in/Karachi?format=j1`
-   - This returns JSON format weather data
-
-2. **Extract Temperature**: From the JSON response, extract the current temperature in Celsius from the `current_condition` section.
-
-3. **Return Result**: In your final report, provide:
-   - The current temperature value in Celsius
-   - A brief status message
-   - The raw data for reference
-
-## Expected Output Format
-
-Your final report should include:
-```
-Current Karachi Temperature: [X]°C
-Status: Successfully fetched weather data
-```
-
-## Notes
-
-- Only fetch the temperature, do not perform any transformations
-- Use wttr.in as it provides reliable, free weather data
-- Return just the numeric temperature value clearly

.claude/agents/weather-transformer.md

@@ -1,50 +0,0 @@
----
-name: weather-transformer
-description: Use this agent PROACTIVELY when you need to apply mathematical transformations to temperature data. This agent reads transformation rules from input/input.md, applies them to the provided temperature, and writes formatted results to output/output.md. Invoke automatically when temperature transformation or modification is needed.
-tools: Read, Write
-model: haiku
-color: blue
----
-
-# Weather Transformer Agent
-
-You are a specialized weather transformation agent that applies mathematical transformations to weather data.
-
-## Your Task
-
-You will receive a temperature value and must:
-1. Read transformation instructions from `input/input.md`
-2. Apply the transformation to the temperature
-3. Write the final result to `output/output.md`
-
-## Instructions
-
-1. **Read Transformation Rules**: Use the Read tool to read `input/input.md` which contains the transformation instructions.
-
-2. **Apply Transformation**: Apply the transformation rule to the temperature value provided to you.
-   - Example: If instruction says "add +10", add 10 to the temperature
-   - Example: If instruction says "multiply by 2", multiply temperature by 2
-
-3. **Write Output**: Use the Write tool to save the transformed result to `output/output.md` with proper formatting.
-
-## Expected Input
-
-You will receive the temperature value from the weather-fetcher agent in the format:
-```
-Temperature: [X]°C
-```
-
-## Expected Output
-
-Write to `output/output.md` with format:
-```
-Original Temperature: [X]°C
-Transformation Applied: [description]
-Final Result: [Y]°C
-```
-
-## Notes
-
-- Read the exact transformation from input/input.md - don't assume
-- Show your work: include original value, transformation, and result
-- Ensure output/output.md is properly formatted and readable

.claude/agents/weather.md

@@ -0,0 +1,52 @@
+---
+name: weather
+description: Use this agent PROACTIVELY when you need to fetch and transform weather data for Karachi, Pakistan. This agent fetches real-time temperature from wttr.in API and applies transformation rules from input/input.md, writing results to output/output.md.
+tools: WebFetch, Read, Write
+model: haiku
+color: green
+skills:
+  - weather-fetcher
+  - weather-transformer
+---
+
+# Weather Agent
+
+You are a specialized weather agent that fetches and transforms weather data for Karachi, Pakistan.
+
+## Your Task
+
+Execute the weather workflow by following the instructions from your preloaded skills sequentially:
+
+1. **First**: Follow the `weather-fetcher` skill instructions to fetch the current temperature
+2. **Then**: Follow the `weather-transformer` skill instructions to apply transformations and write results
+
+## Workflow
+
+### Step 1: Fetch Temperature (weather-fetcher skill)
+
+Follow the weather-fetcher skill instructions to:
+- Fetch current temperature from wttr.in API for Karachi
+- Extract the temperature value in Celsius
+- Keep this value for the transformation step
+
+### Step 2: Transform Temperature (weather-transformer skill)
+
+Follow the weather-transformer skill instructions to:
+- Read transformation rules from `input/input.md`
+- Apply the transformation to the fetched temperature
+- Write formatted results to `output/output.md`
+
+## Final Report
+
+After completing both steps, provide a summary:
+- Temperature unit: Celsius
+- Original temperature fetched
+- Transformation rule applied
+- Final transformed result
+- Confirmation that output was written to `output/output.md`
+
+## Critical Requirements
+
+1. **Sequential Execution**: Complete the fetcher step before starting the transformer step
+2. **Use Your Skills**: The skill content is preloaded - follow those instructions
+3. **Data Flow**: Pass the temperature from step 1 to step 2

.claude/commands/weather-orchestrator.md

@@ -0,0 +1,43 @@
+---
+description: Fetch and transform weather data for Karachi
+model: haiku
+---
+
+# Weather Orchestrator Command
+
+Fetch the current temperature for Karachi, Pakistan and apply transformations.
+
+## Workflow
+
+1. Use the AskUserQuestion tool to ask the user whether they want the temperature in Celsius or Fahrenheit
+2. Use the weather agent to fetch and transform the temperature data
+
+## Agent Invocation
+
+Use the Task tool to invoke the weather agent. This agent has two skills preloaded:
+- `weather-fetcher`: Fetches current temperature from wttr.in API
+- `weather-transformer`: Applies transformation rules and writes results
+
+### Invoke Weather Agent
+
+Use the Task tool to invoke the weather agent:
+- subagent_type: weather
+- description: Fetch and transform Karachi weather
+- prompt: Fetch the current temperature for Karachi, Pakistan in [unit requested by user]. Then apply the transformation rules from input/input.md and write the results to output/output.md. The agent has preloaded skills (weather-fetcher and weather-transformer) that provide the detailed instructions.
+- model: haiku
+
+Wait for the agent to complete its workflow.
+
+## Critical Requirements
+
+1. **Use Task Tool Only**: DO NOT use bash commands to invoke agents. You must use the Task tool.
+2. **Single Agent**: The weather agent handles both fetching and transformation using its preloaded skills.
+3. **Pass User Preference**: Include the user's temperature unit preference in the prompt.
+
+## Output Summary
+
+Provide a clear summary to the user showing:
+- Temperature unit requested
+- Original temperature fetched
+- Transformation rule applied (from input/input.md)
+- Final transformed result (written to output/output.md)

.claude/commands/weather.md

@@ -1,14 +0,0 @@
----
-description: Fetch and transform weather data for Karachi
-model: haiku
----
-
-# Weather Command
-
-Execute the weather-karachi skill to fetch and transform temperature data.
-
-Use the Skill tool to execute the `weather-karachi` skill:
-
-```
-Skill(skill="weather-karachi")
-```

.claude/skills/weather-fetcher/SKILL.md

@@ -0,0 +1,36 @@
+---
+name: weather-fetcher
+description: Instructions for fetching current weather temperature data for Karachi, Pakistan from wttr.in API
+---
+
+# Weather Fetcher Skill
+
+This skill provides instructions for fetching current weather data.
+
+## Task
+
+Fetch the current temperature for Karachi, Pakistan in degrees Celsius (Centigrade).
+
+## Instructions
+
+1. **Fetch Weather Data**: Use the WebFetch tool to get current weather data for Karachi from wttr.in API:
+   - URL: `https://wttr.in/Karachi?format=j1`
+   - This returns JSON format weather data
+
+2. **Extract Temperature**: From the JSON response, extract the current temperature in Celsius from the `current_condition` section.
+
+3. **Store Result**: Keep the temperature value for the next step (transformation).
+
+## Expected Output
+
+After completing this skill's instructions:
+```
+Current Karachi Temperature: [X]°C
+Status: Successfully fetched weather data
+```
+
+## Notes
+
+- Only fetch the temperature, do not perform any transformations yet
+- Use wttr.in as it provides reliable, free weather data
+- Return just the numeric temperature value clearly

.claude/skills/weather-karachi/SKILL.md

@@ -1,54 +0,0 @@
----
-name: weather-karachi
-description: Fetch and transform weather data for Karachi. Use when the user asks about Karachi weather, temperature data, or wants to run the weather workflow.
-model: haiku
----
-
-# Weather Karachi Skill
-
-Fetch the current temperature for Karachi, Pakistan and apply transformations.
-
-## Workflow
-
-1. Use the AskUserQuestion tool to ask the user whether they want the temperature in Celsius or Fahrenheit
-2. Use the weather-fetcher subagent to retrieve the current temperature from wttr.in API in the requested unit
-3. Use the weather-transformer subagent to read transformation rules from input/input.md and apply them to the temperature
-4. Write the results to output/output.md
-
-## Subagent Invocation
-
-Use the Task tool to invoke subagents sequentially (not in parallel) to maintain data dependencies.
-
-### Step 1: Fetch Temperature
-
-Use the Task tool to invoke the weather-fetcher subagent:
-- subagent_type: weather-fetcher
-- description: Fetch Karachi temperature
-- prompt: Fetch the current temperature for Karachi, Pakistan in [unit requested by user] from wttr.in API. Return the numeric temperature value in your final report.
-- model: haiku
-
-Wait for the subagent to complete and extract the temperature value from its final report.
-
-### Step 2: Transform Temperature
-
-Use the Task tool to invoke the weather-transformer subagent:
-- subagent_type: weather-transformer
-- description: Transform temperature
-- prompt: Apply transformation rules from input/input.md to the temperature value: [X] degrees. Write formatted results to output/output.md.
-- model: haiku
-
-Wait for the subagent to complete.
-
-## Critical Requirements
-
-1. **Use Task Tool Only**: DO NOT use bash commands to invoke subagents. You must use the Task tool.
-2. **Sequential Execution**: Launch subagents one at a time, wait for completion before launching the next.
-3. **Data Passing**: Extract the temperature from weather-fetcher's report and pass it to weather-transformer's prompt.
-
-## Output Summary
-
-Provide a clear summary to the user showing:
-- Temperature unit requested
-- Original temperature fetched
-- Transformation rule applied (from input/input.md)
-- Final transformed result (written to output/output.md)

.claude/skills/weather-transformer/SKILL.md

@@ -0,0 +1,54 @@
+---
+name: weather-transformer
+description: Instructions for applying mathematical transformations to temperature data based on rules in input/input.md
+---
+
+# Weather Transformer Skill
+
+This skill provides instructions for transforming temperature data.
+
+## Task
+
+Apply mathematical transformations to a temperature value and write results to output file.
+
+## Instructions
+
+1. **Read Transformation Rules**: Use the Read tool to read `input/input.md` which contains the transformation instructions.
+
+2. **Apply Transformation**: Apply the transformation rule to the temperature value.
+   - Example: If instruction says "add +10", add 10 to the temperature
+   - Example: If instruction says "multiply by 2", multiply temperature by 2
+
+3. **Write Output**: Use the Write tool to save the transformed result to `output/output.md` with proper formatting.
+
+## Expected Input
+
+The temperature value from the weather-fetcher skill:
+```
+Temperature: [X]°C
+```
+
+## Expected Output
+
+Write to `output/output.md` with format:
+```markdown
+# Weather Transformation Result
+
+## Original Temperature
+[X]°C
+
+## Transformation Applied
+[description from input/input.md]
+
+## Final Result
+[Y]°C
+
+## Calculation Details
+[X]°C [operation] = [Y]°C
+```
+
+## Notes
+
+- Read the exact transformation from input/input.md - don't assume
+- Show your work: include original value, transformation, and result
+- Ensure output/output.md is properly formatted and readable

CLAUDE.md

@@ -9,13 +9,13 @@ This is a best practices repository for Claude Code configuration, demonstrating
 ## Key Components
 
 ### Weather System (Example Workflow)
-A demonstration of skill-based subagent orchestration:
+A demonstration of the **Command → Agent → Skills** architecture pattern:
-- `/weather` command (`.claude/commands/weather.md`): Entry point, invokes the weather-karachi skill
+- `/weather-orchestrator` command (`.claude/commands/weather-orchestrator.md`): Entry point that invokes the weather agent
-- `/weather-karachi` skill (`.claude/skills/weather-karachi/SKILL.md`): Orchestrates the workflow
+- `weather` agent (`.claude/agents/weather.md`): Executes workflow using preloaded skills
-- `weather-fetcher` subagent: fetches temperature from wttr.in API
+- `weather-fetcher` skill (`.claude/skills/weather-fetcher/SKILL.md`): Instructions for fetching temperature from wttr.in API
-- `weather-transformer` subagent: applies transformation rules from `input/input.md`, writes results to `output/output.md`
+- `weather-transformer` skill (`.claude/skills/weather-transformer/SKILL.md`): Instructions for applying transformation rules from `input/input.md`, writes results to `output/output.md`
 
-Subagents run sequentially via Task tool, not in parallel, to maintain data dependencies.
+The agent has skills preloaded via the `skills` field, providing domain knowledge for sequential execution.
 
 ### Skill Definition Structure
 Skills in `.claude/skills/<name>/SKILL.md` use YAML frontmatter:

docs/AGENTS.md

@@ -1,137 +0,0 @@
-# Subagent Orchestration Best Practices
-
-## Problem: Subagents Not Invoking
-
-### Issue Description
-
-When creating orchestrator skills or subagents that coordinate multiple subagents, a common mistake is using bash commands or other tools instead of the proper `Task` tool to invoke subagents. This results in the subagents not being invoked at all.
-
-### Root Cause
-
-**Incorrect Implementation:**
-
-The orchestrator was trying to use bash commands to invoke subagents:
-- `claude task --agent weather-fetcher "Fetch temperature"`
-
-The problem is that `claude task` is not a valid bash command in the Claude Code environment. Skills and subagents cannot invoke other subagents through bash/CLI commands. Instead, they must use the `Task` tool programmatically.
-
-### Solution
-
-**Correct Implementation:**
-
-1. **Define the skill with proper instructions:**
-
-Skills (in `.claude/skills/<name>/SKILL.md`) orchestrate workflows by invoking subagents via the Task tool:
-
-```yaml
----
-name: weather-karachi
-description: Fetch and transform weather data for Karachi
-model: haiku
----
-```
-
-2. **Use the Task tool properly in the skill's instructions:**
-
-The skill must explicitly instruct to use the Task tool with proper parameters. Instead of vague instructions like "Use the Task tool to launch the weather-fetcher agent", provide specific, clear instructions:
-
-```markdown
-## Step 1: Fetch Temperature
-
-Use the Task tool to invoke the weather-fetcher subagent:
-- subagent_type: weather-fetcher
-- description: Fetch Karachi temperature
-- prompt: Fetch the current temperature for Karachi, Pakistan in Celsius from wttr.in API. Return the numeric temperature value in your final report.
-- model: haiku
-
-Wait for the subagent to complete and extract the temperature value from its final report.
-```
-
-3. **Key Requirements for Orchestrating Subagents:**
-
-   a. **Explicit Tool Usage**: State clearly "DO NOT use bash commands or any other tools. You must use the Task tool to invoke subagents."
-
-   b. **Parameter Specification**: List all required parameters explicitly:
-      - `subagent_type`: The exact subagent name
-      - `description`: A short 3-5 word description
-      - `prompt`: Detailed instructions for the subagent
-      - `model`: The model to use (typically "haiku" for efficiency)
-
-   c. **Sequential Execution**: For sequential workflows, explicitly state "Launch subagents one at a time, wait for completion before launching the next."
-
-   d. **Data Passing**: Provide clear instructions on how to extract data from one subagent's report and pass it to the next subagent's prompt.
-
-### Before and After Comparison
-
-#### Before (Broken):
-```markdown
-## Your Task
-
-1. **Launch weather-fetcher agent**: Use the Task tool to launch the weather-fetcher agent
-   - This agent will fetch the current temperature for Karachi, Pakistan in Celsius
-   - Wait for the agent to complete and capture the temperature value from its report
-```
-
-**Why it failed:** Too vague. The skill interpreted "launch" as running a bash command instead of using the Task tool properly.
-
-#### After (Working):
-```markdown
-## Step 1: Fetch Temperature
-
-Use the Task tool to invoke the weather-fetcher subagent:
-- subagent_type: weather-fetcher
-- description: Fetch Karachi temperature
-- prompt: Fetch the current temperature for Karachi, Pakistan in Celsius from wttr.in API. Return the numeric temperature value in your final report.
-- model: haiku
-
-Wait for the subagent to complete and extract the temperature value from its final report.
-
-## Critical Requirements
-
-1. **Use Task Tool Only**: DO NOT use bash commands or any other tools. You must use the Task tool to invoke subagents.
-```
-
-**Why it works:**
-- Explicitly lists all Task tool parameters
-- Clearly states NOT to use bash commands
-- Provides specific parameter values
-
-### Testing the Fix
-
-After creating the skill, test it by invoking:
-
-```bash
-# Via skill invocation
-/weather-karachi
-
-# Or via Skill tool from another command
-Skill(skill="weather-karachi")
-```
-
-The skill should now:
-1. Successfully invoke weather-fetcher using the Task tool
-2. Extract the temperature from the fetcher's report
-3. Invoke weather-transformer with the temperature value
-4. Report the complete workflow results
-
-### Key Takeaways
-
-1. **Skills and subagents cannot use CLI commands to invoke other subagents** - they must use the Task tool programmatically
-2. **Be explicit with tool usage** - clearly state which tool to use and which tools NOT to use
-3. **Provide complete parameter specifications** - list all required parameters with example values
-4. **Test orchestrator skills thoroughly** - ensure they properly chain subagent invocations
-5. **Use clear, unambiguous language** - avoid terms like "launch" or "run" which could be interpreted as bash commands
-
-### Color Configuration
-
-The `color` parameter in subagent frontmatter (e.g., `color: green`) controls the color of the subagent's output in the CLI, making it easier to visually distinguish between different subagents' outputs. This is purely a display feature and does not affect the subagent's functionality or the content it produces.
-
-## Skills vs Commands vs Subagents
-
-| Component | Location | Purpose | Invocation |
-|-----------|----------|---------|------------|
-| **Skill** | `.claude/skills/<name>/SKILL.md` | Orchestrate workflows, reusable procedures | `/skill-name` or `Skill(skill="name")` |
-| **Command** | `.claude/commands/<name>.md` | Legacy format (still works), simple procedures | `/command-name` |
-| **Subagent** | `.claude/agents/<name>.md` | Specialized task execution with isolated context | `Task(subagent_type="name", ...)` |
-
-Skills are recommended over commands as they support additional features like supporting files, invocation control, and subagent execution.

docs/COMPARISION.md

@@ -1,337 +0,0 @@
-# COMPARISION
-commands, agents, skill
-
-# Invocation Patterns Reference
-
-This document provides a comprehensive reference for invoking Agents, Commands, and Skills across different contexts.
-
-## Agent Invocation
-
-Agents are specialized subprocesses that handle complex, multi-step tasks. They support both **automatic delegation** (proactive) and **explicit invocation**.
-
-### Invocation Methods
-
-  | From                 | How                    | Example                             | Notes |
-  |----------------------|------------------------|-------------------------------------|-------|
-  | Claude CLI           | **Automatic (proactive)** | User: "I just modified the auth code"<br/>Claude auto-invokes code-review agent | Requires "PROACTIVELY" keyword in agent description |
-  | Claude CLI           | Explicit natural language | "use weather transformer agent to transform 50 degree" | Direct request by name |
-  | /commands/Commands.md| Task tool              | `Task(subagent_type="weather-transformer", description="Transform temperature", prompt="Apply transformation to 50°C", model="haiku")` | Programmatic invocation from commands |
-  | Another subagent     | Task tool              | `Task(subagent_type="weather-fetcher", description="Fetch temperature", prompt="Get Karachi temperature", model="haiku")` | Agent-to-agent orchestration |
-
-### Automatic Delegation (Proactive Agents)
-
-Agents can be configured for **automatic invocation** by Claude based on context. Claude analyzes:
-- Your task description and request
-- Each agent's `description` field
-- Current context and available tools
-
-**To enable automatic delegation**, include directive keywords in the agent's `description` field:
-- `"use PROACTIVELY"`
-- `"MUST BE USED"`
-- `"Invoke automatically"`
-
-**Example: Proactive Code Review Agent**
-```yaml
----
-name: code-reviewer
-description: Use this agent PROACTIVELY after any code modifications. Expert code reviewer that analyzes quality, security, and maintainability. Invoke automatically when code is written or modified.
-tools: Read, Grep, Bash
-model: haiku
----
-```
-
-**Result**: When you modify code, Claude automatically invokes `code-reviewer` without explicit request.
-
-**Example: Proactive Test Agent**
-```yaml
----
-name: test-runner
-description: MUST BE USED when tests fail or new code is added. Automatically runs tests and fixes failures.
-tools: Bash, Read, Edit
-model: haiku
----
-```
-
-**Result**: Claude proactively runs tests after code changes.
-
-## Command Invocation
-
-Commands (slash commands) are user-defined operations that extend Claude Code with reusable prompts. They support both **automatic invocation** (by default) and **explicit activation**.
-
-### Invocation Methods
-
-  | From                 | How                    | Example                             | Notes |
-  |----------------------|------------------------|-------------------------------------|-------|
-  | Claude CLI           | **Automatic (default)** | User: "I need to write unit tests"<br/>Claude auto-invokes `/write-unit-test` if description matches | Requires `description` field; can disable with `disable-model-invocation: true` |
-  | Claude CLI           | Natural language prompt | "use the weather command to fetch the weather" | Claude interprets and expands command |
-  | Claude CLI           | Explicit slash command  | `/weather-karachi` | Direct command execution |
-  | /agents/Agents.md    | SlashCommand tool      | `SlashCommand(command="/weather-karachi")` | Commands invoked from agents |
-  | Another /command     | SlashCommand tool      | `SlashCommand(command="/weather-karachi")` | Command chaining |
-
-### Automatic Command Invocation
-
-By default, Claude can **automatically invoke slash commands** through the SlashCommand tool when contextually appropriate. This works similarly to proactive agents.
-
-**How it works:**
-- Commands with a `description` field are included in Claude's context
-- Claude analyzes your request and matches it against available command descriptions
-- If a match is found, Claude automatically invokes the command via SlashCommand tool
-
-**To enable automatic invocation**, ensure your command has a clear `description`:
-```yaml
----
-description: Writes comprehensive unit tests for the specified function or module
-model: haiku
----
-```
-
-**To disable automatic invocation** for a specific command:
-```yaml
----
-description: Administrative command for system configuration
-disable-model-invocation: true
-model: haiku
----
-```
-
-**Example: Auto-invoked Test Command**
-```yaml
----
-description: Generates and runs unit tests for new code. Use when user adds new functions or asks about testing.
-model: haiku
----
-```
-
-**Result**: When you say "I added a new login function", Claude may automatically invoke this command.
-
-**Global Control**: Use `/permissions` to disable the SlashCommand tool entirely, preventing all automatic command execution.
-
-## Skill Invocation
-
-Skills are model-invoked capabilities that Claude activates automatically based on context. Unlike agents and commands, skills cannot be explicitly invoked.
-
-  | From                 | How                    | Example                             | Notes |
-  |----------------------|------------------------|-------------------------------------|-------|
-  | Claude CLI           | Automatic (model-driven) | User: "Extract text from this PDF"<br/>Claude autonomously activates PDF skill | No explicit invocation - Claude decides based on Skill description |
-  | Claude CLI           | Natural language prompt | "Can you help me analyze this Excel file?"<br/>Claude may invoke Excel skill if available | Context-dependent activation |
-  | /agents/Agents.md    | Skill tool             | `Skill(command="pdf")` | **Only if agent has Skill tool access** |
-  | Another /command     | Skill tool             | `Skill(command="xlsx")` | **Only if command prompt includes Skill tool access** |
-  | Another skill        | N/A                    | Skills cannot invoke other skills | Skills are single-purpose and don't orchestrate |
-
-### Key Differences: Skills vs Agents vs Commands
-
-| Feature              | Agent                  | Command                | Skill                  |
-|----------------------|------------------------|------------------------|------------------------|
-| **Invocation**       | **Both**: Automatic (with PROACTIVELY keyword) OR Explicit (Task tool/prompt) | **Both**: Automatic (default, via SlashCommand tool) OR Explicit (slash syntax) | Automatic only (model-driven) |
-| **User Activation**  | Contextual (if proactive) OR "Use X agent" | Contextual (default) OR `/command-name` | Contextual request only |
-| **Discoverability**  | Automatic via description (if proactive) OR user must know name | Automatic via description (default) | Automatic via description |
-| **Orchestration**    | Can invoke other agents/commands | Can invoke agents/commands | Single-purpose, no orchestration |
-| **Configuration**    | Use `PROACTIVELY` keyword in description for auto-invocation | `disable-model-invocation: true` to prevent auto-invocation | Description determines when to activate |
-| **Opt-Out**          | Don't use PROACTIVELY keyword | Set `disable-model-invocation: true` | No opt-out mechanism |
-| **Best For**         | Multi-step workflows   | Reusable procedures    | Ambient capabilities   |
-
-## Invocation Examples by Scenario
-
-### Scenario 1: User Wants Weather Data
-
-**Using Skill (Explicit):**
-```
-User: /weather-karachi
-Result: Explicit skill execution → subagents run → output generated
-```
-
-**Using Skill (Automatic - Default Behavior):**
-```yaml
-# Skill configuration with description (automatic invocation enabled by default)
-# Location: .claude/skills/weather-karachi/SKILL.md
----
-name: weather-karachi
-description: Fetch and transform weather data for Karachi. Use when the user asks about Karachi weather.
-model: haiku
----
-```
-```
-User: "What's the weather like in Karachi?"
-Result: Claude automatically invokes weather-karachi skill via Skill tool
-Note: Skills are auto-invoked by default unless disable-model-invocation: true is set
-```
-
-**Using Subagent (Explicit):**
-```
-User: "Use the weather-fetcher agent to get Karachi temperature"
-Result: Claude invokes weather-fetcher subagent → returns temperature
-```
-
-**Using Subagent (Automatic/Proactive):**
-```yaml
-# Subagent configuration with PROACTIVELY keyword
----
-description: Use this agent PROACTIVELY when user asks about Karachi weather.
-             Fetch current temperature from wttr.in.
----
-```
-```
-User: "What's the weather like in Karachi?"
-Result: Claude automatically invokes weather-fetcher subagent → returns temperature
-Note: Subagent description contains "PROACTIVELY" keyword
-```
-
-**Using Command (Legacy):**
-```
-User: /weather
-Result: Command invokes weather-karachi skill via Skill tool
-Note: Commands still work but skills are recommended
-```
-
-### Scenario 2: Orchestrating Multiple Steps
-
-**Skill Orchestrating Subagents:**
-```markdown
-<!-- In .claude/skills/weather-karachi/SKILL.md -->
-1. Task(subagent_type="weather-fetcher", ...)
-2. Task(subagent_type="weather-transformer", ...)
-```
-
-**Command Invoking Skill:**
-```markdown
-<!-- In /weather command -->
-Skill(skill="weather-karachi")
-```
-
-**Subagent Orchestrating Other Subagents:**
-```markdown
-<!-- In weather-orchestrator subagent -->
-1. Task(subagent_type="weather-fetcher", ...)
-2. Extract temperature from report
-3. Task(subagent_type="weather-transformer", prompt="Transform {temperature}", ...)
-```
-
-### Scenario 3: Automatic Agent Invocation (Real-World)
-
-**Proactive Code Review Agent:**
-```yaml
----
-name: code-reviewer
-description: Use this agent PROACTIVELY after any code modifications. Reviews for quality, security, and best practices.
-tools: Read, Grep, Bash
----
-```
-
-**User Workflow:**
-```
-User: "I've updated the authentication logic in auth.ts"
-Claude: Automatically invokes code-reviewer agent
-Agent: Reads auth.ts, analyzes changes, reports findings
-User: Gets automatic code review without asking for it
-```
-
-**Proactive Test Runner Agent:**
-```yaml
----
-name: test-runner
-description: MUST BE USED when code is modified or tests fail. Automatically runs tests and reports results.
-tools: Bash, Read
----
-```
-
-**User Workflow:**
-```
-User: "I fixed the login bug"
-Claude: Automatically invokes test-runner agent
-Agent: Runs test suite, reports pass/fail status
-User: Gets immediate test feedback
-```
-
-### Scenario 4: From Within Code/Prompts
-
-**Invoking Subagent from Skill:**
-```markdown
-Use the Task tool to invoke the weather-fetcher subagent:
-- subagent_type: weather-fetcher
-- description: Fetch Karachi temperature
-- prompt: Fetch the current temperature for Karachi, Pakistan in Celsius
-- model: haiku
-```
-
-**Invoking Skill from Command:**
-```markdown
-Use the Skill tool to execute the weather-karachi skill:
-Skill(skill="weather-karachi")
-```
-
-**Invoking Skill from Another Skill:**
-```markdown
-Use the Skill tool to invoke a related skill:
-Skill(skill="data-processor")
-```
-
-## Core Differences Between Commands and Agents
-
-While commands and agents share similar invocation patterns, they have fundamental architectural differences:
-
-### Key Architectural Differences
-
-**1. Purpose & Complexity**
-- **Commands**: Reusable prompt templates that expand into instructions. Best for **procedural workflows** with predefined steps.
-- **Agents**: Autonomous subprocesses with their own tool access. Best for **complex, multi-step tasks** requiring independent decision-making.
-
-**2. Execution Model**
-- **Commands**: Expand into prompts that Claude executes in the main conversation context
-- **Agents**: Run as separate subprocesses with isolated execution environments
-
-**3. Tool Access**
-- **Commands**: Execute within the main Claude context and inherit available tools
-- **Agents**: Have explicitly defined tool subsets specified in their configuration (e.g., `tools: Read, Grep, Bash`)
-
-**4. Autonomy Level**
-- **Commands**: Provide instructions for Claude to follow. Can interact with users via AskUserQuestion tool to gather preferences or clarify requirements.
-- **Agents**: Act autonomously to complete tasks and return final reports. **Should NOT ask questions** - they run independently and must work with the information provided in their prompt.
-
-**5. Model Selection**
-- **Commands**: Can specify which model to use for executing the command
-- **Agents**: Can specify which model runs the agent subprocess (e.g., `model: haiku` for cost efficiency)
-
-### When to Choose Each
-
-**Choose Commands when:**
-- You have a reusable prompt/workflow
-- Steps are mostly predefined
-- You want users to trigger via `/slash` syntax
-- You need a simple procedural template
-
-**Choose Agents when:**
-- Task requires autonomous multi-step problem solving
-- You need isolated tool access for security/organization
-- Task should run as independent subprocess
-- You want specialized capabilities (like code review, test running)
-
-**Example from this repository:**
-- `/weather-karachi` skill: Orchestrates the workflow (`.claude/skills/weather-karachi/SKILL.md`)
-- `/weather` command: Entry point that invokes the skill (`.claude/commands/weather.md`)
-- `weather-fetcher` subagent: Autonomous subprocess that fetches temperature
-- `weather-transformer` subagent: Autonomous subprocess that transforms data
-
-The skill coordinates, while subagents execute their specialized tasks independently.
-
-## Summary
-
-- **Agents**: **Both automatic and explicit invocation**
-  - Automatic: Use `PROACTIVELY` or `MUST BE USED` keywords in description field
-  - Explicit: Via Task tool or natural language prompt
-
-- **Commands**: **Both automatic (default) and explicit invocation**
-  - Automatic: Enabled by default when `description` field is present
-  - Explicit: Via slash syntax (`/command`) or SlashCommand tool
-  - Opt-out: Set `disable-model-invocation: true` to prevent automatic invocation
-
-- **Skills**: **Automatic invocation only** - Claude decides based on context and description
-  - No explicit invocation mechanism
-  - No opt-out available
-
-- **Key Design Choices**:
-  - Use **proactive agents** for complex multi-step workflows that should trigger automatically
-  - Use **commands (with auto-invocation)** for reusable procedures that should activate contextually
-  - Use **commands (with disable-model-invocation)** for workflows requiring strict explicit control
-  - Use **skills** for ambient, always-available single-purpose capabilities
-  - **Orchestration difference**: Agents and commands can orchestrate other agents/commands; skills are single-purpose
-

docs/weather-flow-architecture.md

@@ -4,7 +4,10 @@ This document describes the complete flow of the weather data fetching and trans
 
 ## System Overview
 
-The weather system consists of skills and specialized subagents that work together to fetch and transform temperature data for Karachi, Pakistan.
+The weather system demonstrates the **Command → Agent → Skills** architecture pattern, where:
+- A command orchestrates the workflow
+- An agent executes tasks using preloaded skills
+- Skills provide domain-specific knowledge and instructions
 
 ## Flow Diagram
 
@@ -14,108 +17,100 @@ The weather system consists of skills and specialized subagents that work togeth
 └─────────────────────────────────────────────────────────────────┘
                               │
                               ▼
-                    ┌──────────────────┐
+                    ┌──────────────────────┐
-                    │  /weather        │
+                    │  /weather-orchestrator│
-                    │  Command         │
+                    │  Command              │
-                    └──────────────────┘
+                    │  (Entry point)        │
+                    └──────────────────────┘
                               │
-                              │ invokes via Skill tool
+                              │ Task tool invocation
                               ▼
-                    ┌──────────────────┐
+                    ┌──────────────────────┐
-                    │ /weather-karachi │
+                    │  weather             │
-                    │  Skill           │
+                    │  Agent               │
-                    └──────────────────┘
+                    │  (Orchestrates flow) │
+                    │                      │
+                    │  skills:             │
+                    │  - weather-fetcher   │
+                    │  - weather-transformer│
+                    └──────────────────────┘
                               │
-                              │ Step 1 (Sequential via Task tool)
+              ┌───────────────┴───────────────┐
-                              ▼
+              │                               │
-                  ┌────────────────────────┐
+              ▼                               ▼
-                  │  weather-fetcher       │
+┌─────────────────────────┐     ┌─────────────────────────┐
-                  │  Subagent              │
+│  weather-fetcher        │     │  weather-transformer    │
-                  │  (subagent_type)       │
+│  Skill                  │     │  Skill                  │
-                  └────────────────────────┘
+│  (Preloaded knowledge)  │     │  (Preloaded knowledge)  │
-                              │
+└─────────────────────────┘     └─────────────────────────┘
-                              ▼
+              │                               │
-                  ┌────────────────────────┐
+              ▼                               ▼
-                  │  wttr.in API           │
+┌─────────────────────────┐     ┌─────────────────────────┐
-                  │  Fetch Temperature     │
+│  wttr.in API            │     │  input/input.md         │
-                  │  for Karachi           │
+│  Fetch Temperature      │     │  Read Transform Rules   │
-                  └────────────────────────┘
+│  for Karachi            │     └─────────────────────────┘
-                              │
+└─────────────────────────┘                   │
-                              │ Returns: 26°C
+              │                               ▼
-                              ▼
+              │ Returns: 26°C       ┌─────────────────────────┐
-                              │
+              │                     │  Apply Transform        │
-                              │ Step 2 (Sequential via Task tool)
+              └─────────────────────│  26 + 10 = 36°C         │
-                              ▼
+                                    └─────────────────────────┘
-                  ┌─────────────────────────┐
+                                              │
-                  │  weather-transformer    │
+                                              ▼
-                  │  Subagent               │
+                                    ┌─────────────────────────┐
-                  │  (subagent_type)        │
+                                    │  output/output.md       │
-                  └─────────────────────────┘
+                                    │  Write Results          │
-                              │
+                                    └─────────────────────────┘
-                              ▼
+                                              │
-                  ┌─────────────────────────┐
+                                              ▼
-                  │  input/input.md         │
+                                    ┌─────────────────────────┐
-                  │  Read Transform Rules   │
+                                    │  Display Summary        │
-                  └─────────────────────────┘
+                                    │  to User                │
-                              │
+                                    └─────────────────────────┘
-                              │ Reads: "add +10"
-                              ▼
-                  ┌────────────────────────┐
-                  │  Apply Transform       │
-                  │  26 + 10 = 36°C        │
-                  └────────────────────────┘
-                              │
-                              ▼
-                  ┌────────────────────────┐
-                  │  output/output.md      │
-                  │  Write Results         │
-                  └────────────────────────┘
-                              │
-                              ▼
-                  ┌────────────────────────┐
-                  │  Display Summary       │
-                  │  to User               │
-                  └────────────────────────┘
 ```
 
 ## Component Details
 
-### 1. Skills and Commands
+### 1. Command
 
-#### `/weather` (Command)
+#### `/weather-orchestrator` (Command)
-- **Location**: `.claude/commands/weather.md`
+- **Location**: `.claude/commands/weather-orchestrator.md`
 - **Purpose**: Entry point for weather operations
-- **Action**: Invokes `weather-karachi` skill via Skill tool
+- **Action**: Invokes the weather agent via Task tool
 - **Model**: haiku
 
-#### `/weather-karachi` (Skill)
+### 2. Agent with Skills
-- **Location**: `.claude/skills/weather-karachi/SKILL.md`
+
-- **Purpose**: Orchestrates the weather fetching and transformation workflow
+#### `weather` (Agent)
-- **Action**: Launches two specialized subagents sequentially via Task tool
+- **Location**: `.claude/agents/weather.md`
+- **Purpose**: Execute the weather workflow using preloaded skills
+- **Skills**: `weather-fetcher`, `weather-transformer`
+- **Tools Available**: WebFetch, Read, Write
 - **Model**: haiku
+- **Color**: green
 
-### 2. Specialized Subagents
+The agent has skills preloaded into its context at startup. It follows the instructions from each skill sequentially.
 
-#### `weather-fetcher`
+### 3. Skills
-- **Location**: `.claude/agents/weather-fetcher.md`
+
-- **Purpose**: Fetch real-time temperature data
+#### `weather-fetcher` (Skill)
+- **Location**: `.claude/skills/weather-fetcher/SKILL.md`
+- **Purpose**: Instructions for fetching real-time temperature data
 - **Data Source**: wttr.in API for Karachi, Pakistan
 - **Output**: Temperature in Celsius (numeric value)
-- **Tools Available**: WebFetch
 
-#### `weather-transformer`
+#### `weather-transformer` (Skill)
-- **Location**: `.claude/agents/weather-transformer.md`
+- **Location**: `.claude/skills/weather-transformer/SKILL.md`
-- **Purpose**: Apply mathematical transformations to temperature data
+- **Purpose**: Instructions for applying mathematical transformations
 - **Input Source**: `input/input.md` (transformation rules)
 - **Output Destination**: `output/output.md` (formatted results)
-- **Tools Available**: Read, Write
 
-### 3. Data Files
+### 4. Data Files
 
 #### `input/input.md`
 - **Purpose**: Stores transformation rules
 - **Format**: Natural language instructions (e.g., "add +10 in the result")
-- **Access**: Read by weather-transformer subagent
+- **Access**: Read by weather agent following weather-transformer skill
 
 #### `output/output.md`
 - **Purpose**: Stores formatted transformation results
@@ -127,15 +122,17 @@ The weather system consists of skills and specialized subagents that work togeth
 
 ## Execution Flow
 
-1. **User Invocation**: User runs `/weather` command or `/weather-karachi` skill
+1. **User Invocation**: User runs `/weather-orchestrator` command
-2. **Skill Invocation**: `/weather` invokes `weather-karachi` skill via Skill tool
+2. **User Prompt**: Command asks user for preferred temperature unit (Celsius/Fahrenheit)
-3. **Sequential Subagent Execution** (via Task tool):
+3. **Agent Invocation**: Command invokes weather agent via Task tool
-   - **Step 1**: `weather-fetcher` subagent fetches current temperature from wttr.in
+4. **Skill Execution** (within agent context):
-   - **Step 2**: `weather-transformer` subagent:
+   - **Step 1**: Agent follows `weather-fetcher` skill instructions to fetch temperature from wttr.in
-     - Reads transformation rules from `input/input.md`
+   - **Step 2**: Agent follows `weather-transformer` skill instructions to:
-     - Applies rules to the fetched temperature
+     - Read transformation rules from `input/input.md`
-     - Formats and writes results to `output/output.md`
+     - Apply rules to the fetched temperature
-4. **Result Display**: Summary shown to user with:
+     - Write formatted results to `output/output.md`
+5. **Result Display**: Summary shown to user with:
+   - Temperature unit requested
    - Original temperature
    - Transformation rule applied
    - Final transformed result
@@ -143,25 +140,51 @@ The weather system consists of skills and specialized subagents that work togeth
 ## Example Execution
 
 ```
-Input: /weather
+Input: /weather-orchestrator
-├─ Invokes: weather-karachi skill (via Skill tool)
+├─ Asks: Celsius or Fahrenheit?
-│  ├─ Subagent: weather-fetcher (via Task tool)
+├─ User: Celsius
-│  │  └─ Result: 26°C
+├─ Task: weather agent (via Task tool)
-│  ├─ Subagent: weather-transformer (via Task tool)
+│  ├─ Skills Preloaded:
+│  │  ├─ weather-fetcher (knowledge)
+│  │  └─ weather-transformer (knowledge)
+│  ├─ Step 1 (weather-fetcher skill):
+│  │  └─ Fetches from wttr.in → 26°C
+│  ├─ Step 2 (weather-transformer skill):
 │  │  ├─ Reads: input/input.md ("add +10")
 │  │  ├─ Calculates: 26 + 10 = 36°C
 │  │  └─ Writes: output/output.md
-│  └─ Output:
+│  └─ Returns: Complete report
-│     ├─ Original: 26°C
+└─ Output:
-│     ├─ Transform: Add +10
+   ├─ Unit: Celsius
-│     └─ Result: 36°C
+   ├─ Original: 26°C
+   ├─ Transform: Add +10
+   └─ Result: 36°C
 ```
 
 ## Key Design Principles
 
-1. **Separation of Concerns**: Each component has a single, clear responsibility
+1. **Command → Agent → Skills**: Three-tier architecture for clean separation
-2. **Sequential Execution**: Subagents run in order to ensure data dependencies are met
+2. **Skills as Knowledge**: Skills provide domain knowledge preloaded into agent context
-3. **Specialized Subagents**: Task-specific subagents with minimal tool access
+3. **Single Agent**: One agent handles multiple related tasks using its skills
-4. **Skill-Based Architecture**: Skills orchestrate workflows, subagents execute tasks
+4. **Sequential Execution**: Agent follows skill instructions in order
 5. **Configurable Transformations**: Rules stored externally in input files
 6. **Structured Output**: Results formatted consistently in output files
+
+## Architecture Pattern: Agent-Skills
+
+This system demonstrates the **agent-skills pattern** where:
+
+```yaml
+# In agent definition (.claude/agents/weather.md)
+---
+name: weather
+skills:
+  - weather-fetcher
+  - weather-transformer
+---
+```
+
+- **Skills are preloaded**: Full skill content is injected into agent's context at startup
+- **Agent uses skill knowledge**: Agent follows instructions from preloaded skills
+- **No dynamic invocation**: Skills are not invoked separately; they're reference material
+- **Single execution context**: All work happens within one agent's context

input/input.md

@@ -1 +1 @@
-add +10 in the result.
+add +20 in the result.

output/output.md

@@ -1,3 +1,13 @@
-Original Temperature: 24°C
+# Weather Transformation Result
-Transformation Applied: add +10 in the result
+
-Final Result: 34°C
+## Original Temperature
+24°C
+
+## Transformation Applied
+Add +20 to the temperature value
+
+## Final Result
+44°C
+
+## Calculation Details
+24°C + 20 = 44°C