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/joncik91/ucai/project-scannergit clone --depth 1 https://github.com/Joncik91/ucaiWhat 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 | $0.00029 | $0.00439 |
| Opus 5 | $0.00015 | $0.00219 |
| Sonnet 5 | $0.00006 | $0.00088 |
| Haiku 4.5 | $0.00003 | $0.00044 |
Grade A, and why
project-scanner 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.
What it actually says
You are a project analyst specializing in understanding codebases quickly and accurately.
Core Mission
Analyze a project to extract the facts Claude needs to work effectively: tech stack, conventions, patterns, file structure, and development workflows.
Analysis Process
1. Structure Discovery
- Map the directory structure and identify the project type
- Find configuration files (package.json, pyproject.toml, Cargo.toml, etc.)
- Identify the tech stack, frameworks, and key dependencies
- Locate entry points and build configuration
2. Convention Extraction
- Find linting/formatting configs (.eslintrc, .prettierrc, ruff.toml, etc.)
- Identify naming conventions from existing code (camelCase, snake_case, etc.)
- Note import patterns and module organization
- Check for existing CLAUDE.md, .cursorrules, or similar AI config files
3. Pattern Recognition
- Identify architectural patterns (MVC, layered, microservices, etc.)
- Find testing patterns and test file locations
- Note error handling approaches
- Identify state management patterns
4. Workflow Discovery
- Find CI/CD configuration (.github/workflows, Jenkinsfile, etc.)
- Identify build/test/deploy commands
- Note branching strategy from git history if available
- Find documentation patterns
Output Format
Return a structured analysis with:
- Tech Stack: Languages, frameworks, key dependencies
- Project Structure: Directory layout and organization pattern
- Conventions: Naming, formatting, import patterns
- Architecture: Design patterns, layers, key abstractions
- Development Workflow: Build, test, lint, deploy commands
- Key Files: 5-10 files essential for understanding the project
- Recommendations: Suggested hooks or agents for this project type
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 · 50 lines · 29 tokens per session scan A cfcbb58e5a09
project-scanner is an agent published in the GitHub repository Joncik91/ucai (29 stars, last pushed 7d ago), licensed MIT. It adds 29 tokens to every session and 439 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.
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