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 agents/catch-the-wave/fullstack-ios-claude-skills/codebase-analyzergit clone --depth 1 https://github.com/catch-the-wave/fullstack-ios-claude-skillsWhat 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 | $0.00055 | $0.01481 |
| Opus 5 | $0.00028 | $0.00740 |
| Sonnet 5 | $0.00011 | $0.00296 |
| Haiku 4.5 | $0.00006 | $0.00148 |
Grade A, and why
codebase-analyzer 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 — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Core Principle: Institutional Memory > One-off Analysis
Every analysis updates a knowledge file that future runs build on. Never start from zero.
<quick_start>
-
Check: Does
.claude/CODEBASE.mdexist?- No → Full Scan mode
- Yes → Update mode
-
Full Scan: Glob entry points → Read architecture → Grep patterns → Find smells → Create knowledge file
-
Update: Read existing →
git diff→ Update changed sections → Add timestamp </quick_start>
<success_criteria>
.claude/CODEBASE.mdcreated/updated with current timestamp- Architecture mapped (2-5 bullet points with file refs)
- Patterns documented in table format
- Smells categorized by severity (HIGH/MED/LOW) with checkboxes
- Decisions captured with rationale and source
- Output report shows key findings and recommendations </success_criteria>
-
Detect stack — Language, framework, database, infrastructure
Glob: "**/main.py", "**/index.ts", "**/package.json", "**/requirements.txt" -
Map architecture — Entry points, feature structure, data flow
Read: main entry files Glob: "**/router*.py", "**/routes/**", "**/api/**" -
Identify patterns — What conventions does this codebase follow?
Grep: "@router|@app|Depends|BaseModel" Grep: "repository|service|schema" -
Find smells — DRY violations, god files, unclear boundaries
# Find large files find . -name "*.py" -exec wc -l {} + | sort -rn | head -20 -
Document decisions — From comments, commit history, docs
Grep: "# TODO|# HACK|# NOTE|# Why" -
Create knowledge file — Sharp observations only
Write: .claude/CODEBASE.md (see template in references/)
-
Read existing knowledge
Read: .claude/CODEBASE.md -
Check what changed
git diff --name-only HEAD~10 # Or since last analysis date from CODEBASE.md -
Read changed files
Read: [changed files from diff] -
Update affected sections
- Architecture: if entry points or structure changed
- Patterns: if new conventions discovered
- Smells: add new, mark fixed with [x]
- Decisions: if new rationale found
-
Update timestamp
**Last analyzed:** [current date]
- Verify file exists and is readable
- Check markdown structure is parseable (has expected ## sections)
- If corrupted or malformed:
- Back up to
.claude/CODEBASE.md.backup - Recreate with full scan
- Back up to
After creating/updating:
- Verify all required sections present
- Check file:line references are valid
- Ensure no duplicate smells entries
<knowledge_file>
Location: .claude/CODEBASE.md (in project root)
Template: See references/knowledge-file-template.md
Required Sections:
| Section | Content | Format |
|---|---|---|
| Architecture | Entry points, structure, data flow | 2-5 bullets |
| Patterns | Conventions with file:line refs | Table |
| Smells | Issues with severity | Checkbox list |
| Decisions | Why things are this way | Table |
| API Surface | Key endpoints by feature | Grouped list |
| Dependencies | External services | Table |
Quality Rules:
- Sharp, not verbose — Each bullet is actionable
- File:line references — Always cite specific locations
- Severity levels — HIGH/MED/LOW for smells
- Checkbox for smells —
[ ]open,[x]fixed - Tables over prose — Scannable > readable
- Update timestamps — Know when analysis is stale </knowledge_file>
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 · 211 lines · 55 tokens per session scan A 05380b477846
codebase-analyzer is an agent published in the GitHub repository catch-the-wave/fullstack-ios-claude-skills (5 stars, last pushed 8mo ago), licensed MIT. It adds 55 tokens to every session and 1,481 once invoked, about $0.0003 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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