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/britt/agent-skills/project-analysisnpx skills add britt/agent-skills --skill project-analysisgit clone --depth 1 https://github.com/britt/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/britt/agent-skills/project-analysis)<a href="https://agentmods.dev/skills/britt/agent-skills/project-analysis"><img src="https://agentmods.dev/badge/skills/britt/agent-skills/project-analysis.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00040 | $0.00992 |
| Opus 5 | $0.00020 | $0.00496 |
| Sonnet 5 | $0.00008 | $0.00198 |
| Haiku 4.5 | $0.00004 | $0.00099 |
Grade A, and why
project-analysis 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 4d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Analysis Skill
Perform comprehensive analysis of a project codebase to understand its structure, architecture, key files, and dependencies.
When to Use
Activate when:
- User asks "analyze this project" or "what does this codebase look like?"
- Starting work on an unfamiliar codebase
- Reviewing project architecture before making changes
- Generating documentation about project structure
- Understanding dependency landscape
When NOT to use: For questions about a single file or feature, just read the relevant file directly — a full analysis is overkill.
Analysis Workflow
Step 1: Survey the Codebase
Build a high-level overview using standard filesystem operations:
- List the directory tree with
lsor Glob to see top-level structure - Read manifest files to identify the stack:
package.json,go.mod,pyproject.toml,Cargo.toml,Gemfile,pom.xml, etc. - If useful, count files by extension to gauge language distribution, e.g.
find . -name '*.ts' -not -path '*/node_modules/*' | wc -l
Step 2: Understand Project Type
Based on what the survey found, identify the project type:
| Indicator | Project Type |
|---|---|
| package.json + React/Next.js | Web application |
| package.json + Express/Fastify | API server |
| Cargo.toml | Rust project |
| pyproject.toml / setup.py | Python project |
| go.mod | Go project |
| Dockerfile + docker-compose | Containerized service |
| index.ts + bin/ | CLI tool |
Step 3: Read Key Files
Examine critical files:
Always check:
README.md- Project purpose and documentationpackage.json/Cargo.toml/pyproject.toml- Dependencies and metadata
Check if they exist:
tsconfig.json/vite.config.ts/webpack.config.js- Build configurationDockerfile/docker-compose.yml- Container setup.env.example- Environment variablesCONTRIBUTING.md- Development workflow
Step 4: Explore Architecture
List key directories (src/, lib/, app/, etc.) to understand component organization, then identify architectural patterns:
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.
- 4d ago First seen · 126 lines · 40 tokens per session scan A 91761fcf4d1d
project-analysis is a skill published in the GitHub repository britt/agent-skills (5 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 992 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…