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/tpavanipradeep/everything-claude-code/code-reviewgit clone --depth 1 https://github.com/tpavanipradeep/everything-claude-codeWhat 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 | $0.00010 | $0.00390 |
| Opus 5 | $0.00005 | $0.00195 |
| Sonnet 5 | $0.00002 | $0.00078 |
| Haiku 4.5 | $0.00001 | $0.00039 |
Grade A, and why
code-review 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.
This is a copy
100% identical to code-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Code Review Command
Review code changes for quality, security, and maintainability: $ARGUMENTS
Your Task
- Get changed files: Run
git diff --name-only HEAD - Analyze each file for issues
- Generate structured report
- Provide actionable recommendations
Check Categories
Security Issues (CRITICAL)
- Hardcoded credentials, API keys, tokens
- SQL injection vulnerabilities
- XSS vulnerabilities
- Missing input validation
- Insecure dependencies
- Path traversal risks
- Authentication/authorization flaws
Code Quality (HIGH)
- Functions > 50 lines
- Files > 800 lines
- Nesting depth > 4 levels
- Missing error handling
- console.log statements
- TODO/FIXME comments
- Missing JSDoc for public APIs
Best Practices (MEDIUM)
- Mutation patterns (use immutable instead)
- Unnecessary complexity
- Missing tests for new code
- Accessibility issues (a11y)
- Performance concerns
Style (LOW)
- Inconsistent naming
- Missing type annotations
- Formatting issues
Report Format
For each issue found:
**[SEVERITY]** file.ts:123
Issue: [Description]
Fix: [How to fix]
Decision
- CRITICAL or HIGH issues: Block commit, require fixes
- MEDIUM issues: Recommend fixes before merge
- LOW issues: Optional improvements
IMPORTANT: Never approve code with security vulnerabilities!
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 · 69 lines · 10 tokens per session scan A 0a4687d21a13
code-review is a command published in the GitHub repository tpavanipradeep/everything-claude-code (103 stars, last pushed 5mo ago), licensed MIT. It adds 10 tokens to every session and 390 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to code-review, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.