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Found 1,812 Skills
Read, write, and manipulate SEG-Y seismic data files. Fast C library with Python bindings for trace, header, inline, and crossline access. Use when Claude needs to: (1) Read/inspect SEG-Y files, (2) Extract trace data or headers, (3) Access 3D survey data by inline/crossline, (4) Create new SEG-Y files from arrays, (5) Modify existing SEG-Y files, (6) Extract subsets of seismic data, (7) Read/write Seismic Unix format.
Generates production-ready Python code following PEP standards, type hints, and clean code principles. Use when user requests Python implementation of classes, functions, services, or modules. Triggers on "implement", "write", "Python code", "create class", "create function", "code for".
Install and configure the official Gladia SDKs (@gladiaio/sdk for JS/TS, gladiaio-sdk for Python). Use when the user asks about SDK setup, client initialization, API key configuration, choosing between JS and Python, browser usage, retry/timeout settings, error handling, or SDK vs raw API decisions. The SDK is the recommended default for all Gladia integrations.
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*).
Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard, tracking SLA compliance, classifying third-party risk, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Triggers on "vendor SLA", "vendor scorecard", "third-party risk", "TPRM", "vendor review", "SaaS audit", "supplier performance", "vendor health check", "renewal review". Forks context so large vendor catalogs (50-500 line items) and SLA logs don't pollute the parent thread. Ships 3 stdlib-only Python tools (vendor scorer with industry tuning, SLA compliance tracker with credit-claim flags, vendor risk classifier across 4 risk vectors), 3 reference docs each citing 7+ authoritative sources (Gartner / Shared Assessments / NIST / ISO 27036 / breach post-mortems), and a 5-vendor catalog template. Distinct from c-level-advisor/general-counsel-advisor (contract law, not operational management), business-growth/contract-and-proposal-writer (outbound proposals, not inbound vendor scoring), and sibling procurement-optimizer (spend categorization, not vendor performance).
Build Docker images for Python services following team conventions. Use this skill when writing Dockerfiles, authoring CI image build pipelines, or adding a new service — covers mitodl image naming, git short-ref tags, relocatable uv venvs, and shared library handling.
Write, push, run, publish, and manage Kaggle Benchmark tasks using the kaggle CLI and the kaggle-benchmarks Python SDK. Use when the user wants to create or push a benchmark task (optionally with attached Kaggle datasets), run benchmarks against LLM models, check task/run status, stream or fetch execution logs, download results and source notebooks, publish a task to make it public, or troubleshoot benchmark workflows.
Queries Huawei Cloud identity and access management resources (IAM) via read-only Python SDK. Covers users, groups, policies, agencies, AK/SK, MFA devices, login/password/ACL policies, security compliance, and account quotas. No write operations. Use this skill when the user needs to query IAM identity info, check policies/permissions, view agency details, or inspect AK/SK/MFA status. Triggers: IAM, 用户, 用户组, 策略, 委托, 权限, AK/SK, MFA, 密码策略, 安全合规, 身份查询, 身份认证, identity, policy, agency.
Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.
Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Two responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, and (2) run ruff against any Python files Claude has just generated or edited. Stops at "the touched files pass `ruff check`." TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run on the touched files; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and the project has no `ruff.toml` at its root yet — drop the bundled template; (3) the user asks about lint, format, docstring style, or reaches for `black` / `isort` / `flake8` / `pydocstyle` (redirect to ruff — the stack's canonical linter, owned by `data-science-python-stack` Tier 1). SKIP when: the project is non-Python; the only edits in this turn are to Markdown / TOML / JSON / YAML; the file lives in a third-party vendored directory the user doesn't own. HOW TO USE: run ruff manually on the files you just touched — do not configure a PostToolUse hook for this. **Read the "Stop conditions" block and emit the Pre-flight checklist as visible text in your response — both are mandatory before running ruff.**
Solve LP, MILP, QP (beta) with cuOpt Python API — linear/quadratic objectives, integer variables, scheduling, portfolio, least squares.
A shared, file-based town square where multiple coding agents talk, coordinate, and debate — no server required. Use whenever more than one agent works the same repo (parallel Claude Code or Codex sessions, separate git worktrees, a fleet splitting a task) and they must stay out of each other's way or think together. TRIGGER on phrasings like "coordinate with the other agent/session", "post to / check the agora", "ask the other agents", "leave a message for whoever's working on X", "announce what files you're touching", "is anyone else editing this?", or any time you're about to edit shared code while other agents are live. Also trigger when an agent is stuck and wants a peer's second opinion, or when several agents each drafted a design (an API, a schema, an architecture) and the group needs to compare the proposals and converge on the best one. Works for any agent that can run a Python script, not just Claude Code.