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/florianbruniaux/claude-code-plugins/explaingit clone --depth 1 https://github.com/FlorianBruniaux/claude-code-pluginsWhat 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 | $0.00939 |
| Opus 5 | $0.00008 | $0.00469 |
| Sonnet 5 | $0.00003 | $0.00188 |
| Haiku 4.5 | $0.00002 | $0.00094 |
Grade A, and why
explain scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Explainer
Explain code, concepts, or system behavior with adjustable depth levels.
Purpose
Get clear explanations of:
- How specific code works
- Why certain patterns are used
- What a system/module does
- Architectural decisions and trade-offs
Instructions
Step 1: Determine Scope
Identify what needs explanation:
- File: Entire file structure and purpose
- Function/Method: Specific implementation details
- Concept: Architectural pattern or design decision
- Flow: How data/control moves through the system
Step 2: Assess Complexity
Simple (1-2 min read) → Quick summary, key points only
Standard (3-5 min read) → Purpose, how it works, key decisions
Deep (10+ min read) → Full breakdown, alternatives, trade-offs
Step 3: Gather Context
# For file explanations
head -50 "$FILE" # See imports and structure
# For function explanations
grep -A 30 "function $NAME\|def $NAME\|fn $NAME" "$FILE"
# For module explanations
ls -la "$DIR"
cat "$DIR/index.ts" 2>/dev/null || cat "$DIR/__init__.py" 2>/dev/null
Step 4: Structure the Explanation
Output Format
📖 Explanation: [Target]
Scope: [file/function/concept/flow] Depth: [simple/standard/deep]
What It Does
[1-3 sentences describing the purpose]
How It Works
[Step-by-step breakdown appropriate to depth level]
Key Decisions
| Decision | Why | Alternative |
|---|---|---|
| [choice made] | [reasoning] | [what else could work] |
Example Usage
// How to use this correctly
Related Code
path/to/related.ts- [relationship]path/to/dependency.ts- [relationship]
💡 Learning Notes (if --learn flag)
[Additional context for understanding the broader pattern]
Depth Levels
Simple (/explain --simple)
**validateUser()** checks if the user object has required fields
(email, password) and returns a boolean. Uses regex for email format.
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 · 173 lines · 15 tokens per session scan A 6524ea6808ea
explain is a command published in the GitHub repository FlorianBruniaux/claude-code-plugins (40 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 939 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
content-generate
Social media content generation command. Produces ready-to-use posts, captions, visual briefs, and hashtags for the given platform and type.
api-doc
API documentation generation. Scans route definitions and produces structured API docs.
aso
App Store Optimization command. iOS app listing analysis via the iTunes API, keyword optimization, and competitor comparison.
changelog
Automatic changelog generation. Produces a structured changelog from commit history.
coach
Coaching analysis command. Performs data-driven work-pattern analysis and offers personal improvement suggestions.
competitive-intel
Competitive analysis command. Analyzes the market, competitors, and opportunities with a comprehensive competitive-intelligence framework.