Loading...
Loading...
Found 373 Skills
Ultra-lightweight channel for refactor processes - used when changes are obviously too small to justify the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step HUMAN verification required. Trigger scenarios: When the user says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip all those steps", and the scope of changes is clearly limited to a single function/single component, with tests available for self-validation.
Meeting notes page — title bar with attendees, agenda checklist, decisions block, action items table with owners + dates, and a "next meeting" footer. Use when the brief mentions "meeting notes", "minutes", "1:1 notes", "all-hands recap", or "会议纪要".
Assess IT vendors and third-party partners with multi-factor risk scoring and regulatory compliance checklists. Use when evaluating technology vendors.
Prepare for and respond to SEC and FINRA regulatory examinations across the full exam lifecycle. Use when the user asks about exam notification letters, document request lists, deficiency letter responses, mock examination programs, annual compliance reviews under Rule 206(4)-7, or SEC/FINRA examination priorities. Also trigger when users mention 'we just got an exam letter', 'preparing for our first SEC exam', 'how to respond to a deficiency finding', 'staff interview preparation', 'what does OCIE look for', 'examination readiness checklist', 'sweep exam on off-channel comms', or ask what to expect during a regulatory audit.
Turn Steam store-page, wishlist, demo, Next Fest, and launch-window ambiguity into one packet-first Steam launch brief. Use when an indie dev, small studio, founder-marketer, or publisher helper needs to decide whether the next move is a page-promise audit, wishlist-signal check, demo-readiness gate, event-timing workback, or launch-ops runbook — especially when they say "help my Steam page", "wishlists are weak", "is our demo ready", "should we do Next Fest", or "give me a Steam launch checklist". Route broad non-game GTM work to `marketing-automation` and player-feedback/build-performance issues to the game specialist skills.
Guides people operations (HR ops)—employee lifecycle administration, HRIS workflows, onboarding and offboarding checklists, handbook and policy rollout, benefits and payroll coordination, performance review cycles, leave and PTO process, and people data hygiene. Use when running new-hire onboarding, offboarding, HR policy communications, performance cycle logistics, org change updates in HRIS, or employee-facing process design—not for corporate board governance (corporate-counsel), commercial contract redlines (commercial-counsel), SOC audit evidence (compliance-engineer), or customer success onboarding (customer-ops-specialist). Escalate employment law questions to qualified counsel.
Performs a comprehensive security review of code changes in a GitHub PR or issue. Checks out the branch, analyzes changed files against a 9-category security checklist, and produces PASS/WARNING/FAIL verdicts. Use when reviewing pull requests for security vulnerabilities, hardcoded secrets, injection flaws, auth bypasses, or insecure configurations. Trigger keywords - security review, code review, appsec, vulnerability assessment, security audit, review PR security.
Claude Code skill (trtllm-agent-toolkit): implement or extend TensorRT-LLM AutoDeploy fusion transforms under transform/library/ in a TensorRT-LLM checkout. Prefer existing kernels and custom ops; use Triton only when no viable existing-kernel path exists. Use ad-graph-dump for AD_DUMP_GRAPHS_DIR workflows. Covers TRT-LLM paths, registry, default.yaml registration, graph validation, tests, and a review checklist — without prescribing profiling tools or throughput targets.
Use when a Head of Ops, Knowledge Manager, or TPM-Internal needs to author, validate, or clean up company SOPs and internal runbooks (procurement intake, vendor offboarding, incident-comms cascade, employee onboarding, expense reimbursement, system-access provisioning, customer-escalation playbook) — including 5W2H completeness checks (Who-What-When-Where-Why-How-HowMuch), cross-link and orphan-page validation across a sprawling Notion/Confluence/Obsidian wiki, KB ingestion + hygiene reporting, ops onboarding doc generation, and runbook step verification (named owner, expected duration, observable success signal, rollback path, escalation contact). Pairs Kaoru Ishikawa's 5W2H method, Atul Gawande's *The Checklist Manifesto*, ISO 9001, ITIL v4 Service Operation, FDA 21 CFR Part 211, and Google SRE Workbook runbook discipline with deterministic stdlib-only Python tools that score completeness, detect anti-patterns, and emit prioritized cleanup lists. Distinct from `engineering/llm-wiki` (Karpathy-style personal PKM second brain), `engineering-team/runbook-generator` (system-ops production debugging runbook), `project-management/*` (Jira/Confluence delivery + ticket tracking), and sibling `business-operations/process-mapper` (BPMN process *design*, while knowledge-ops is process *documentation*).
Draft a demand letter from a completed intake, gated on a privilege / FRE 408 / waiver / admission checklist, with a .docx output, post-send checklist, and an offer to create a matter. Use when the user says "draft the demand", "write the [type] letter", or has a finished demand intake ready to turn into a sendable draft.
Use this skill when planning a product launch, feature announcement, or release strategy. Trigger phrases include: "plan our product launch," "write a launch plan," "Product Hunt launch strategy," "launch checklist," "pre-launch preparation," "waitlist strategy," "launch email sequence," "beta launch vs public launch," "PR for our launch," "launch day execution," "post-launch follow-through."
Decide where files live in an ML experimentation project: reusable code in `src/<pkg>/`, one `# %%` script per experiment in `experiments/`, design notes + index in `journal/`, reports in `reports/`, agent-only probes in `scratch/`, narrative digest in `overview/summary.md`. Owns the layout, the file-creation rules (one file per experiment, ask before editing), and the jupytext `# %%` script convention. Never imposes `data/` — the user owns that. TRIGGER — any of: - Starting a new ML project / scaffolding a workspace. - About to create the first experiment file in a project. - About to create `src/<pkg>/data.py` / `features.py` / `pipeline.py` / `evaluate.py` for the first time. - About to write a `.ipynb` for experimentation — redirect to a `# %%` script under `experiments/`. - User asks where something should live, how to organize the project, or how to set up the workspace. - About to add a new experiment iteration — decide new file vs edit existing (ask the user). SKIP when: the file is clearly part of an already-populated module (e.g., adding a function to existing `features.py`); pure refactor inside a single existing file; pipeline declaration mechanics (`build-ml-pipeline`); evaluation mechanics (`evaluate-ml-pipeline`); skore symbol lookup (`python-api`). HOW TO USE: **first run the Detection table** below — if any signal matches, glue to existing conventions (do not rename or move folders). If no signal matches, scaffold the default layout. **Emit the Pre-flight checklist as visible text and read the Stop conditions before any file is created or edited.** Use templates in `templates/`; copy and adapt, do not rewrite from scratch.