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 skills/quangphu1912/codebase-analyzer/analyzing-code-qualitynpx skills add quangphu1912/codebase-analyzer --skill analyzing-code-qualitygit clone --depth 1 https://github.com/quangphu1912/codebase-analyzerWhat 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 | $0.00031 | $0.00695 |
| Opus 5 | $0.00015 | $0.00347 |
| Sonnet 5 | $0.00006 | $0.00139 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
analyzing-code-quality 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 yesterday.
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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Announce at start: "Using codebase-analyzer to analyze code quality."
Overview
Identify quality patterns, anti-patterns, complexity hotspots, and risk areas that make code hard to maintain.
Process
- Find hotspots: files changed most frequently via git log
- Detect anti-patterns: god classes, long methods, deep nesting, feature envy (see references/anti-pattern-catalog.md)
- Check error handling consistency
- Assess naming conventions and readability
- Estimate test coverage indicators (test-to-source ratio, test file presence)
- Find complexity hotspots (deep nesting, long functions)
Quick Reference
| Anti-Pattern | Detection | Risk |
|---|---|---|
| God class | >500 lines, >15 methods | High |
| Long method | >50 lines | Medium |
| Deep nesting | >4 levels of if/for | High |
| Feature envy | Method uses another class more than its own | Medium |
| Duplicated code | Similar blocks in 3+ files | Medium |
| Missing error handling | try/catch absent around IO | High |
Trigger Signals
- HIGH confidence: Code generation artifacts (header comments, generated markers) ->
trace-codebase-provenance - HIGH confidence: Build-time code injection patterns ->
analyze-build-pipeline - MEDIUM confidence: High churn files with complex logic -> refactoring priority
- LOW confidence: Normal quality patterns -> no deep dive needed
Quality-Churn Correlation
A file that changes frequently AND has high complexity is a bug factory. A file that changes frequently but is simple is just a configuration hub. The CORRELATION is the insight, not the individual metrics. Use git log --format='%H' --name-only to find high-churn files, then cross-reference with complexity. For churn analysis commands, see _shared/references/git-archaeology-techniques.md.
Quality Gradients
Code quality degrades from edges inward. Entry points and API handlers are polished. Internal services and data access layers accumulate debt. Check the gradient to find where debt hides. A codebase that is clean at the edges but rotten in the middle has a steeper remediation curve than one with uniform moderate quality.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 66 lines · 31 tokens per session scan A 76981480ec15
analyzing-code-quality is a skill published in the GitHub repository quangphu1912/codebase-analyzer (2 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 695 once invoked, about $0.0002 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 2026-08-31.
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