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/lftpadilla/agent-dev-kit/semgrepnpx skills add LFTPadilla/agent-dev-kit --skill semgrepgit clone --depth 1 https://github.com/LFTPadilla/agent-dev-kitWhat 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 | $0.00062 | $0.00479 |
| Opus 5 | $0.00031 | $0.00239 |
| Sonnet 5 | $0.00012 | $0.00096 |
| Haiku 4.5 | $0.00006 | $0.00048 |
Grade A, and why
semgrep 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
semgrep — static analysis / SAST
Pattern-based static analysis. Deterministic, fast, rule-driven — the complement to an LLM security review: semgrep never misses a known pattern, the LLM reasons about novel ones. Run both.
Run
semgrep --config auto # auto-select rules for the detected languages
semgrep --config p/typescript # registry rule pack (TS)
semgrep --config p/javascript
semgrep --config p/owasp-top-ten # OWASP Top 10 patterns
semgrep --config p/secrets # hardcoded secrets
semgrep --config p/nodejs # Node-specific
semgrep --config auto --json # machine-readable for processing
Scope to a diff for speed:
semgrep --config auto $(git diff --name-only --diff-filter=ACM main)
Install: pipx install semgrep (or brew install semgrep). No global install? pipx run semgrep ....
How to use the output
- Pick rule packs by the code under review —
p/owasp-top-ten+p/secretsfor auth/payment surfaces;p/typescriptfor general correctness. - Triage findings by severity. Confirm each against the real code — semgrep patterns can false-positive on guarded paths.
- For a PR, scan only the diff (above) to keep it fast.
- Report: rule id, file:line, why it matters, fix. Don't auto-apply on security code without confirmation.
Gotchas
--config autophones the registry; for offline/CI pin explicitp/...packs.- Custom rules go in
.semgrep.yml— but prefer registry packs first (YAGNI). - Pairs with the
security-reviewskill: semgrep catches known patterns, the review reasons about the rest.
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 · 47 lines · 62 tokens per session scan A d699f295c132
semgrep is a skill published in the GitHub repository LFTPadilla/agent-dev-kit (2 stars, last pushed 4d ago), licensed MIT. It adds 62 tokens to every session and 479 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.
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.
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…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
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.