Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/thedecipherist/claude-code-mastery/explaingit clone --depth 1 https://github.com/TheDecipherist/claude-code-masteryWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00015 | $0.00442 |
| Opus 5 | $0.00008 | $0.00221 |
| Sonnet 5 | $0.00003 | $0.00088 |
| Haiku 4.5 | $0.00002 | $0.00044 |
Grade A, and why
explain scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Explain Code
Provide a clear, thorough explanation of the specified code.
Input
The user will provide one of:
- A file path:
/explain src/auth/jwt.ts - A file path with line range:
/explain src/auth/jwt.ts:45-80 - A function/class name:
/explain parseToken - Just
/explain— explain the currently open or most recently discussed file
Explanation Structure
1. Overview (2-3 sentences)
What does this code do at a high level? What problem does it solve?
2. Key Components
Break down the major parts:
## Function: functionName
**Purpose:** One sentence description
**Parameters:**
- `param1` (type) — what it's for
- `param2` (type) — what it's for
**Returns:** What and when
**Side effects:** Any mutations, API calls, state changes
3. Control Flow
Explain the execution path:
- First, it does X
- Then checks Y
- If Y is true, Z happens
- Otherwise, W happens
Use a simple flowchart for complex logic:
Input → Validate → Transform → Output
↓
Error → Log → Return null
4. Dependencies
What does this code depend on?
- External libraries
- Internal modules
- Environment variables
- Database/API connections
5. Gotchas & Edge Cases
Things that might surprise someone:
- Non-obvious behavior
- Edge cases handled (or not handled)
- Performance considerations
- Known limitations
6. Usage Example
Show how to use this code:
// Example usage
const result = functionName(arg1, arg2);
Tone
- Assume the reader is a competent developer unfamiliar with this specific code
- Avoid jargon unless defining it
- Use "this code" not "the code" for clarity
- Be concise but complete
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 87 lines · 15 tokens per session scan A 99b50c974897
explain is a command published in the GitHub repository TheDecipherist/claude-code-mastery (545 stars, last pushed 3mo ago), licensed MIT. It adds 15 tokens to every session and 442 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
handoff
Write a session handoff document for the next agent or session.
cleanup
Autonomous cleanup-loop iteration: discover ONE target → complete execution → verify → report. Runs stateless: derive from current tree; assume prior runs left it consistent.
validate-2
Run comprehensive end-to-end validation of the Remote Agentic Coding Platform including Docker, Test Adapter, Database, and full GitHub workflow execution.
build-unity
Build Unity project (WebGL, Desktop, or PSG1).
deploy
Deploy Solana program (devnet first, then mainnet).
generate-idl-client
Generate TypeScript client from Solana program IDL using Codama or Anchor.