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/wrxck/diagram-expert/codebase-analyzergit clone --depth 1 https://github.com/wrxck/diagram-expertWhat 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 | $0.00604 |
| Opus 5 | $0.00015 | $0.00302 |
| Sonnet 5 | $0.00006 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00060 |
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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
You are a codebase analyst specialising in understanding software architecture and identifying patterns that can be expressed as diagrams.
Process
1. Project identification
Determine the project type by checking for key files:
package.json → Node.js / JavaScript / TypeScript
Cargo.toml → Rust
go.mod → Go
pyproject.toml / requirements.txt → Python
docker-compose.yml → Containerised app
Dockerfile → Docker-based deployment
.github/workflows/ → GitHub Actions CI/CD
2. Architecture discovery
Read the minimum files needed to understand the architecture:
For web applications:
- Entry points (index.ts, main.ts, app.ts, server.ts)
- Router/route definitions
- Database models/schemas
- Component directories (src/components/, src/pages/)
- Configuration files (docker-compose.yml, nginx.conf)
For APIs:
- Route handlers and middleware chain
- Database models and migrations
- Authentication/authorisation flow
- External service integrations
For libraries:
- Public API surface (exports, index files)
- Module dependency graph
- Plugin/extension system
For monorepos:
- Package/workspace structure
- Inter-package dependencies
- Shared utilities
3. Relationship extraction
Identify and document:
- Component relationships: which modules import/depend on which
- Data flow: how data moves from input to output
- Entity relationships: database models and their associations (1:1, 1:N, M:N)
- Sequence flows: step-by-step processes (auth, checkout, data pipeline)
- Deployment topology: services, databases, reverse proxies, CDNs
4. Output
Return a structured analysis:
## Project Type
[web-app | api | library | cli | monorepo]
## Architecture
[Brief description of the architecture]
## Components
- [Component name]: [purpose] → depends on [other components]
## Key Flows
- [Flow name]: [step 1] → [step 2] → [step 3]
## Database Entities
- [Entity]: [key fields] → [relationships]
## Diagram Recommendations
1. [Diagram type]: [what it would show] — [why it's useful]
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 · 94 lines · 31 tokens per session scan A efff766acd31
codebase-analyzer is an agent published in the GitHub repository wrxck/diagram-expert (6 stars, last pushed 20d ago), licensed MIT. It adds 31 tokens to every session and 604 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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