From eb74fba9229027fd0e6f982bc96fb4f4ee8ba212 Mon Sep 17 00:00:00 2001 From: Shayan Rais Date: Thu, 30 Apr 2026 18:54:15 +0500 Subject: [PATCH] =?UTF-8?q?add=20claude-code-best-practice=20deck=20?= =?UTF-8?q?=E2=80=94=20canonical=20reusable=20fork=20from=20GDG=20event=20?= =?UTF-8?q?deck?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Forked from presentation/2026-04-25-gdg-kolachi-cli-claude-code-gemini/index.html on 2026-04-30 to serve as the ongoing main reference deck. Renamed and decoupled from GDG/Gemini-specific branding: - title tag, slide-1 H1, subtitle, and HTML banner all read "Claude Code Best Practice" - favicon swapped from gemini-jumping.svg to claude-jumping.svg - right-corner global Gemini mascot removed (left Claude mascot kept) - GDG event badge replaced with neutral GitHub repo badge - four trailing Gemini-comparison slides removed (49, 50, 51, 52) - co-presenter intro slide removed - inline banners fully repaired (1:1 with data-slide values) Final deck: 48 slides ending with "Thank you" closing slide. Co-Authored-By: Claude --- .../claude-code-best-practice/index.html | 2477 +++++++++++++++++ 1 file changed, 2477 insertions(+) create mode 100644 presentation/claude-code-best-practice/index.html diff --git a/presentation/claude-code-best-practice/index.html b/presentation/claude-code-best-practice/index.html new file mode 100644 index 0000000..84d807a --- /dev/null +++ b/presentation/claude-code-best-practice/index.html @@ -0,0 +1,2477 @@ + + + + + + + Claude Code Best Practice + + + +
+ + + +
+ + +

Claude Code Best Practice

+ + +

+ Practical patterns for + + Claude + Claude Code + +

+ + +
github.com/shanraisshan/claude-code-best-practice
+ +
+ + + + +
+
+ + +
+ Shayan Rais +
+ + +

Shayan Rais

+

Software Architect at disrupt.com

+ + +
+ + +
+
Education
+ +
+ FAST NUCES logo +
+
Master’s in Computer Science
+
FAST NUCES — 2019
+
+
+ +
+ +
+ NED University logo +
+
Bachelor’s in Computer Information Systems
+
NED University — 2014
+
+
+
+ + + + Claude mascot +
+
Contributions
+
Creator of claude-code-best-practice
+
The most starred 🇵🇰 Pakistani AI repo GitHub with almost 50,000 stars ★
+
+ + +
+
+ +
+ + + + +
+
+ claude-code-best-practice GitHub stars growth +
+
+ + + + +
+

🚨 Problem Statement

+ + +

Fetch weather of Karachi

+ + +
    +
  1. Single source of truth
    2. +
  2. Repetitively
    3. +
+ + +
+
+

By solving this problem statement, we’ll learn different concepts of agentic engineering along the way.

+
+
+
+ + + + +
+

Jargon you'll hear

+

I'll unpack each of these as we go — for now, just let them wash over you.

+
+ + + + agentic engineering + + + progressive disclosure + + + orchestration + + + dumb zone + + + agentic workflows + + + harness + + + compaction + + + context window + + + ralph wiggum loop + + + + MCP + + + hooks + + + + context rot + + + prompt engineering + + + AI slop + + + inference + + + + hallucination + + + context bloat + + + one-shot prompting + + + token burn + + + vibe coding + + +
+ scroll for glossary ↓ +
+
+ + +
+ +
+

progressive disclosure — feeding the AI only what it needs right now, not everything upfront

+

orchestration — coordinating several AI agents like a conductor leads a band

+

dumb zone — the stretch where AI has too much context and starts thinking worse, not better

+

agentic workflows — AI that plans, acts, checks its work, and adapts — multi-step on its own

+

harness — the scaffolding around the model — files, terminal, tools — that turns a chatbot into a worker

+

compaction — auto-summarizing old chat so the AI keeps going without hitting its memory ceiling

+

context window — the AI’s working memory — how much it can “see” at once before older details fall off

+

ralph wiggum loop — when the AI repeats the same broken step in circles, like a confused kid who can’t stop

+

MCP — a universal adapter letting AI talk to your tools (GitHub, Slack, databases)

+

hooks — auto-triggers that run your rules before or after the AI does anything

+
+ +
+

context rot — quality decay as the conversation drags on and earlier details blur

+

prompt engineering — the craft of phrasing requests so the AI understands exactly what you mean

+

AI slop — low-effort, generic AI output that looks polished but says nothing

+

inference — the moment the model actually runs to produce an answer. Training is when the model learned (once, long ago). Inference is the model answering you, right now

+

hallucination — when AI confidently makes up facts that sound true but aren’t

+

context bloat — overstuffing the AI’s memory so it slows down and loses focus

+

one-shot prompting — giving the AI one example and asking it to follow the same pattern

+

token burn — wasting expensive AI “words” on unnecessary back-and-forth or bloated prompts

+

vibe coding — describing what you want in plain English and hoping the AI nails it

+

agentic engineering — building guardrails so AI acts like a reliable teammate, not a gamble

+
+
+ +
+ + + + +
+
+

Difference between GPT and ChatGPT?

+

discuss

+
+
+ + + + +
+
+
+ Boris Cherny slides showing the spectrum of Claude Code usage styles +
+ Boris Cherny (creator of Claude Code) — different teams use Claude Code completely differently.
+ There is no single “correct” way. But there are patterns worth understanding. +
+
+
+
+ + + + +
+
+

What is Claude Code?

+

Model (Brain 🧠 — e.g. Opus, GPT) + Harness (Body 💪 — e.g. tools, MCP, memory)

+
+
+ + + + +
+ + +
+
🦜
+

“Stochastic Parrots”

+

Stochastic means random/probabilistic — models don’t know the answer, they sample from a probability distribution.

+
+ + +
+

Prompt:  “The sky is ___”

+ + +
+
blue
+
+
+
+
62%
+
+ + +
+
clear
+
+
+
+
14%
+
+ + +
+
dark
+
+
+
+
8%
+
+ + +
+
falling
+
+
+
+
0.3%
+
+ +

Each run the model samples — temperature controls how widely it samples.

+
+ + +

Bender, Gebru, McMillan-Major, Mitchell — On the Dangers of Stochastic Parrots (2021)

+ + +
+ stochastic + sycophantic + hallucinating + stateless + biased + confident + pattern-matching +
+
+ + + + +
+

🧠 Models — e.g. Opus, GPT, Gemini

+
+
+

✅ Can answer

+

“What is the capital of Japan?”

+

“When did Pakistan gain independence?”

+

“Who wrote Romeo and Juliet?”

+
+
+

❌ Can’t answer

+

“Who won yesterday’s match?”

+

“What’s today’s USD → PKR rate?”

+

“What did Anthropic release yesterday?”

+
+
+

Every model — no matter how new — has a knowledge cut-off. Events after that date simply do not exist inside the model.

+
+
+

Opus 4.7 — Anthropic

+

Knowledge cut-off: January 2026

+

Released 2026-04-17

+
+
+

GPT-5.5 — OpenAI

+

Knowledge cut-off: December 1, 2025

+

Released 2026-04-23 — brand-new, but still has a cut-off.

+
+
+

Gemini 3.1 Pro — Google

+

Knowledge cut-off: January 2025

+

Released 2026-02-19

+
+
+
+ + + + +
+

🧠 Limitations

+

The raw model has no real-time access — no internet, no files, no clock.

+
+ Anthropic Workbench screenshot showing the model refusing a real-time weather query +
+
+ + + + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Control loop + + decides the next call + + Reins + + + + + + + + Tool allowlist + + constrains what it can do + + Bit + + + + + + + + Context management + + narrows what it sees + + Blinders + + + + + + + + Evaluator + + decides when done + + Driver + + + + + + + + State persistence + + carries work forward + + Traces + + + + +

A horse harness. A model harness.

+

The model is the horse. Raw power, no direction. The harness is everything else.

+ +
+
+ + + + +
+

⚡ Tool Calling — how the harness reaches the world

+
+ Diagram showing how Claude sends a tool-call request to the harness, the harness executes it against real-world systems, and the result flows back into Claude’s context +
+
+ + + + +
+

💪 Harness — the body around the brain

+
+
+
🧑‍💼
+

Agents — the specialists

+

A dedicated Claude worker — own context, tools, focus.

+

✅ fresh working memory per run

+
+
+
🎯
+

Skills — the know-how

+

What the specialist (or Claude) can actually do.

+

✅ progressive disclosure — loaded on demand

+
+
+
📘
+

Workflows — the instruction manual

+

Repeatable step-by-step recipes — like an AC install guide.

+

✅ reproducible recipes

+
+
+
📝
+

CLAUDE.md — your memory

+

Knowledge you provide to the model.

+

⚠️ 200-line problem

+
+
+
💭
+

Context — the working memory

+

What Claude holds in his head now — fresh every new chat session.

+
+
+
+
+ 20% of 1M tokens +
+

⚠️ dumb-zone problem

+
+
+
+ + + + +
+

💪 Harness — the body around the brain

+
+
+
✋
+

Tools — the hands

+

Built-in: Read, Edit, Bash, WebSearch.

+
+
+
🔌
+

MCP — the adapters

+

USB-C for AI — plug in external tools (databases, browsers, APIs).

+

e.g. 👁️ Claude in Chrome

+
+
+
🛡️
+

Permissions — the guardrails

+

Allow / ask / deny for tool use.

+
+
+
🪝
+

Hooks — the reflexes

+

Deterministic scripts that fire on events.

+
+
+
📝
+

System Prompt — Claude’s memory

+

Knowledge Anthropic bakes in.

+

e.g. identity · tone · safety

+

✅ always on

+
+
+
+ + + + +
+

🎉 Yayyyyy! Problem solved with harness

+

The harness reaches out via WebSearch and fetches a real answer from live sources.

+
+ Claude Code using Web Search across AccuWeather, Weather25, and TimeAndDate to answer "what is the weather in Karachi?" +
+
+ + + + +
+
+
?
+

Really?

+
+
+ + + + +
+

💪 Non-determinism — Doesn’t always use its tools

+

Similar prompt — but this time the model decided not to use the tool.

+
+ Claude Code refusing to check live weather and asking permission to use WebFetch +
+
+ + + + +
+

💪 Non-determinism — Tools can fail

+

The model first tried one source — it failed (403) — so it fell back to another.

+
+ Claude Code showing a 403 error from timeanddate.com and falling back to wttr.in +
+
+ + + + +
+

🚨 Problem Statement

+
    +
  1. + ❌ Single source of truth +

    The model does not always follow the same path.

    +
    2. +
  2. + ❌ Repetitively +

    Model sometimes failed/forgot to use the tool.

    +
    3. +
+
+ + + + +
+

Vibe Coding

+
+ Andrej Karpathy's Feb 3 2025 tweet coining 'vibe coding' — 'fully give in to the vibes, embrace exponentials, and forget that the code even exists' +
+

Andrej Karpathy — OpenAI founding team · former Director of AI at Tesla · founder of Eureka Labs.

+
+ + + + +
+

Vibe Coding vs Agentic Engineering

+
+
+
# Plain TodoApp +todoapp/ + backend/ + main.py + routes/ + todos.py + users.py + models/ + todo.py + user.py + tests/ + test_todos.py + frontend/ + components/ + TodoList.tsx + Sidebar.tsx + pages/ + index.tsx + todos.tsx + lib/ + api.ts
+
+
+
# With Claude Code Best Practices +todoapp/ + .claude/ # Claude Code config + agents/ # Custom subagents + skills/ # Domain knowledge + commands/ # Slash commands + hooks/ # Lifecycle scripts + rules/ # Modular instructions + settings.json # Team settings + settings.local.json # Personal settings + backend/ + main.py + routes/ + todos.py + users.py + models/ + todo.py + user.py + tests/ + test_todos.py + CLAUDE.md # Backend instructions + frontend/ + components/ + TodoList.tsx + Sidebar.tsx + pages/ + index.tsx + todos.tsx + lib/ + api.ts + CLAUDE.md # Frontend instructions + .mcp.json # Managed MCP servers + CLAUDE.md # Project instructions
+
+
+
+ + + + + + +
+
+

👤 Agents

+
+ /agents +
+

Examples: weather reporter, front-end engineer, QA engineer.

+
+ ✅ Fresh working memory per run + 🎯 Scoped tools, model, permission + ⚡ Parallelizable +
+ 
root/
+├── .claude/
+│   └── agents/
+│       └── weather-agent.md
+└── README.md
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

Create your first agent — /agents

+
+
+
+

The Command

+

Type /agents.

+
+

Opens an interactive menu — pick "Create new agent" and the CLI drafts the agent file for you.

+

Creates .claude/agents/<name>.md — a plain markdown file anyone can edit.

+
+
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

Demo

+ +
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+

🎉 Yayyyyy! Problem solved with agents

+
+ Agent created +
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+
?
+

Not so fast...

+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+

🚨 Problem Statement

+
+
    +
  1. + ✅ Single source of truth +

    The agent will always call the Open-Meteo API — no more source drift.

    +
    2. +
  2. + ❌ Repetitively +

    It’s not guaranteed that Claude will always call this agent.

    +
    3. +
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+

Agent config fields with frontmatter

+
+
+ Field + Description + Enforced by +
+
+ name Recommended + Unique identifier — e.g. weather-agent + harness +
+
+ description Required + When to invoke. Use "PROACTIVELY" for auto-invocation + prompt +
+
+ model + haiku, sonnet, opus, or inherit (default). weather-agent uses sonnet + harness +
+
+ tools + Allowlist of tools. weather-agent allows WebFetch, Read, Write, etc. + harness +
+
+ skills + Skills preloaded into agent context at startup — weather-agent preloads weather-fetcher + harness +
+
+ maxTurns + Maximum agentic turns before the agent stops. weather-agent uses 5 + harness +
+
+ memory + Persistent memory: user, project, or local. weather-agent uses project + harness +
+
+ color + Visual color in task list. weather-agent uses green + harness +
+
+

The skills: field is what makes the agent special. It preloads any-skill directly into the agent’s brain at startup — before the agent has received a single instruction.

+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+

claude-code-best-practice Tips & Tricks

+
+ Claude Code tips and tricks — part 1 +
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+

claude-code-best-practice Tips & Tricks

+
+ Claude Code tips and tricks — part 2 +
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + + + + + +
+
+

📝 CLAUDE.md

+
+ CLAUDE.md +
+

Knowledge you provide to the model — read every session.

+
+ ✅ Loaded into every session + 👥 Team-shareable via git + ⚠️ 200-line problem +
+ 
root/
+├── CLAUDE.md
+└── README.md
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

Create your first CLAUDE.md — /init

+
+
+
+

The Command

+

Type /init in Claude Code.

+
+

Claude scans your codebase and drafts a starter CLAUDE.md for you — project conventions, key patterns, common commands.

+

Creates CLAUDE.md in your repo root — a plain markdown file you edit and commit.

+
+
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

📝 CLAUDE.md — the real thing

+
+ A real CLAUDE.md file showing project rules and agent invocation instructions +
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+

claude-code-best-practice Tips & Tricks

+
+ Claude Code tips and tricks for CLAUDE.md +
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

⚠️ CLAUDE.md problem — keep it under 200 lines

+
+ Illustration of the CLAUDE.md 200-line adherence problem +
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + + + + + +
+
+

🎯 Skills

+
+ .claude/skills/ +
+

Examples: weather fetching, sorting CSV rows, generating SVG cards.

+
+ ✅ Progressive disclosure — loaded on demand + ♻️ Reusable across agents +
+ 
root/
+├── .claude/
+│   └── skills/
+│       └── weather-fetcher/
+│           └── SKILL.md
+└── README.md
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + + + + +
+
+

Create your first skill

+
+
+

Write it by prompting

+

Just describe what you want Claude to do. It drafts the skill file for you.

+

"Create a skill that fetches weather from Open-Meteo for a given city."

+
+
+

Use Anthropic's skill-creator

+

Anthropic ships an official skill-creator skill. Invoke it and it walks you through generating a properly-structured skill.

+

Recommended — always produces the correct SKILL.md format.

+
+
+
+

⚠️ Watch out (method 1)

+

The prompting method sometimes creates the wrong structure. Instead of generating a folder with SKILL.md inside (e.g. weather-fetcher/SKILL.md), it creates a plain weather-fetcher.md file. The wrong form isn’t recognized as a skill by Claude Code.

+
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + + + + +
+
+

🎯 Skills — a real one

+
+ A real skill file on disk — SKILL.md inside a named folder inside .claude/skills/ +
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + + + + +
+

Skill config fields with frontmatter

+

Most fields control how and when the skill loads — enforced by the harness. Only description lives in prompt-land.

+
+
+ Field + Description + Enforced by +
+
+ name Recommended + Display name and /slash-command (defaults to directory name) + harness +
+
+ description Required + When to invoke — used for auto-discovery. Write it clearly. + prompt +
+
+ argument-hint + Autocomplete hint shown in the / menu (e.g. [city-name]) + harness +
+
+ disable-model-invocation + Set true to prevent Claude from invoking this skill automatically + harness +
+
+ user-invocable + Set false to hide from / menu — background knowledge only + harness +
+
+ allowed-tools + Tools allowed without permission prompts when this skill is active + harness +
+
+ model + Model to use when skill is active: haiku, sonnet, opus + harness +
+
+ context + Set to fork to run skill in an isolated subagent context + harness +
+
+

Small description, full body loaded on demand — this is progressive disclosure. Claude’s main context stays lean until the skill is actually needed.

+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + + + + + +
+
+

💭 Context

+
+ /context +
+

The model's working memory — what it can see in this moment.

+
+ ✅ Fresh every chat + ⚠️ Dumb-zone problem + ⚠️ /compact +
+
+
+
+
+ 20% of 1M tokens +
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

🧠 Claude's Brain

+
+

Think of it like this

+

Imagine Claude has a brain that holds everything it's aware of right now — your question, every file it's opened, every tool result, every word it's said back to you. If a thought isn't in the brain, Claude can't use it. Simple as that.

+
+ Context window diagram showing how the 1M token limit is divided across system prompt, tools, files, and conversation +
+
+ 💬 +
+ Your messages + Every question, clarification, and follow-up +
+
+
+ 📄 +
+ Every file Claude opens + Read a 500-page PDF? All of it is in the brain now. +
+
+
+ 🔧 +
+ Every tool result + Web searches, command output, screenshots — all held in memory +
+
+
+
+

Two Things to Know

+

1. The brain is finite. It can hold about 1 million tokens — roughly 750,000 words. Big, but not infinite. 2. The brain empties at the end of every chat. When you start a new conversation, Claude remembers nothing from the last one unless you tell it again.

+
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

What Loads at Session Start

+

The moment you open Claude Code, certain things land in Claude's brain before you've typed a word. The rest waits in the wings — only loaded when you actually need it. This is called progressive disclosure.

+ Diagram showing what loads into Claude's context window at session start +
+
+ 📋 +
+ CLAUDE.md — full content + Standing instructions, every line. Always pinned in the brain at startup. +
+
+
+ 🎓 +
+ Skills — descriptions only + Claude knows which skills exist and what each does — the full content loads when the skill is actually invoked. +
+
+
+ 👤 +
+ Agents — descriptions only + The roster of specialists. The full system prompt loads when the agent is dispatched. +
+
+
+
+

The One-Liner

+

Only descriptions of skills and agents are loaded at startup — the rest is fetched on-demand. That's progressive disclosure. It keeps the brain light.

+
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

📄 Lost in the Middle

+

by Nelson F. Liu · Stanford University · 2023

+ +
+ +
+ Lost in the Middle paper illustration showing U-shaped attention curve across context positions +
+ + +
+
    +
  1. + Primacy & recency work. + Information at the start of the context (what Claude sees first) and at the end (what Claude saw most recently) gets strong attention. These are the safe zones. +
    2. +
  2. + The middle is the dumb zone. + Content buried in the middle of a long context effectively disappears. The model has the tokens, but doesn't weight them strongly during generation. It's in the working memory — but not really read. +
    3. +
  3. + Practical implication. + Keep critical instructions either at the very top (in CLAUDE.md) or near the user's most recent message. A bigger context window doesn't help if your payload lands in the middle. +
    4. +
+ +
+

This is the "dumb-zone problem" the deck has been warning about — now you know where it came from.

+
+
+
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

📘 Workflow

+
+ .claude/commands/ +
+

Repeatable step-by-step recipes — the instruction manual that makes Claude run the same playbook every time.

+
+ ✅ Reproducible recipes + 🔁 Same steps, every run + 👥 Team-shareable via git +
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

📋 Orchestration Workflow

+ Command → Agent → Skill architecture flow +
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + +
+
+

📹 Workflow in action

+
+ Claude running the weather orchestration workflow end-to-end +
+
+
+
+ 🧑‍💼 + Agents + — the specialists + A dedicated Claude worker — own context, own tools, own focus. Each runs in isolation. + ✅ fresh working memory per run +
+
+ 📝 + CLAUDE.md + — your memory + Knowledge you provide to the model. Read every session. Keep it under 200 lines. + ⚠️ 200-line problem +
+
+ 🎯 + Skills + — the know-how + What the specialist (or Claude) can actually do. Loaded on demand — only when needed. + ✅ progressive disclosure +
+
+ 💭 + Context + — the working memory + What Claude holds in his head now — fresh every new chat. Finite budget; compact at ~50%. + ⚠️ dumb-zone problem +
+
+ 📘 + Workflows + — the instruction manual + Repeatable step-by-step recipes — like an AC install guide. Deterministic, reproducible. + ✅ reproducible recipes +
+
+
+ + + + +
+
+

🙏 Thank you!

+
+ Thank you +
+

Questions? Feedback?

+
+ + GitHub + github.com/shanraisshan + +
+
+
+ + + + + +
+ + +
+
1 / --
+
← → or Space to navigate
+ + + +