「check」の検索結果

Research a skill domain before building or improving a skill. Searches academic papers, practitioner blogs, and GitHub skill repos in parallel to find current best practices, domain gotchas, and existing skill patterns. Called by universal-skill-creator and improve-skills before writing any skill. Also load directly when the user asks to research a domain for a skill, find existing skills on a topic, discover best practices for a skill, check what research exists before building an agent skill, or says "what does current research say about", "find best practices for".

日本語の概要は準備中です。原文の説明を表示しています。

Score an unbuilt business idea on desirability, viability, feasibility, distribution wedge, why-now, founder-market-fit, market size, alternatives, defensibility, capital intensity, and regulatory/ethical risk — and return a GO / ITERATE / KILL verdict with kill criteria and a next kill test. Load when the user asks to evaluate a business idea, score a startup idea, screen an idea, decide whether to pursue this venture, do an idea review, or says "is this a good business idea", "should I build this", "evaluate this startup", "screen this idea", "go/no-go on this idea", "kill or pursue". Sub-skill of `venture-exploration`. Calls `fermi` for sizing, `assumption-mapping` for hidden beliefs, optional `pre-mortem` / `adversarial-hat` for high-stakes ideas. Does NOT evaluate built products — for that use `reality-check`.

日本語の概要は準備中です。原文の説明を表示しています。

Seed minimal agent harness v0 — manifest, eval checks stub, governance. AUTO-INVOKED after project-setup or retroactive-project-setup when docs/harness/manifest.json is missing. Also triggers on: generate harness, scaffold agents, agent bootstrap, first time agents in this repo, new project agent setup, set up agent harness, agent onboarding files, missing agent configuration, agent instructions setup, make agents read project rules, agent reliability setup, agents not configured. Pairs with project-setup. Evolution is harness-evolution.

日本語の概要は準備中です。原文の説明を表示しています。

Orchestrator for the learn-from suite - auto-detects source type (academic paper, GitHub repo, blog/web article, or in-conversation learnings) and routes to the correct sub-skill for credibility check, security scan, insight extraction, and application. Load when the user says "learn from", "learn from this", "extract insights from", "apply learnings from", "what can we learn from", or provides a URL, file path, or pasted content that should be ingested as knowledge. Single entry point for all learning workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.

日本語の概要は準備中です。原文の説明を表示しています。

Tactical fast path: turn a small problem, bug report, edit request, or narrow refactor into three deliverables — a brief change-spec (docs/specs/), a detailed implementation-ready plan (docs/plans/), and a TODO.md with agent-pickable tasks and milestones. Load when the user describes a tactical problem and wants quick planning artifacts, says "plan this change", "create a TODO", "write a plan for this", "problem to plan", "break this into tasks for agents", "I want to change X — plan it", or when process-decomposer routes here after determining the user needs lightweight planning deliverables. Also triggers on "create tasks from this problem", "make this actionable", or "turn this into a plan agents can execute". For feature-sized work that needs an executable spec + constitution + cross-check gate, route to `spec-driven-development` (or `feature-spec`) instead.

日本語の概要は準備中です。原文の説明を表示しています。

Extract actionable skill knowledge from academic papers and research articles, assess credibility, run security checks, and either improve existing skills or create new ones. Load when the user asks to learn from a paper, extract insights from a research paper, turn a paper into a skill, apply paper findings to skills, read this paper and improve my skills, or process a research article. Also triggers on "skill from paper", "learn from this paper", "paper to skill", "extract from this research", "apply this paper", or when the user uploads or links to an academic PDF or paper URL.

日本語の概要は準備中です。原文の説明を表示しています。

Orchestrate persistent agent memory across coding sessions, repos, and tools. Load when the user asks to remember, recall context, save project memory, create a handoff, manage global memory, update memory, compact memory, audit memory, forget memory, continue from prior sessions, or before commit/push/git operations that checkpoint project state.

日本語の概要は準備中です。原文の説明を表示しています。

Audit project and global memory for bloat, stale decisions, duplicates, contradictions, unsafe content, missing provenance, broken routing, and over-budget global files. Load when the user asks to audit memory, clean memory, check memory health, or verify memory quality.

日本語の概要は準備中です。原文の説明を表示しています。

Extract actionable insights from blog posts, web articles, and practitioner content - assess credibility, run security checks, and either improve existing skills or apply to the current project. Load when the user asks to learn from an article, extract insights from a blog post, apply a practitioner's findings, or process engineering blog content. Also triggers on "learn from this article", "learn from this blog post", "extract insights from this post", "what can we learn from this article", "apply this article", or when the user links to a blog, Medium, Substack, dev.to, or engineering blog post.

日本語の概要は準備中です。原文の説明を表示しています。

Design automated evaluation pipelines for LLM and agent systems — combining deterministic checks, statistical metrics, and LLM-as-judge scoring into repeatable, CI-integrated eval suites. Load when the user asks to set up automated evals, design an eval pipeline, integrate evals into CI/CD, create an eval suite, do eval-driven development, or says "automate my evals", "CI eval integration", "evaluation pipeline", "continuous evaluation", "monitoring eval quality", "set up regression testing for my agent". Sub-skill of eval-output orchestrator.

日本語の概要は準備中です。原文の説明を表示しています。

Turn a chosen design direction into a canonical DESIGN.md plus production tokens that don't look vibecoded — state-level colors (8-step neutral ramp, rest/hover/active/ disabled, focus ring), APCA-checked contrast, typography, spacing/radius/motion/elevation, an icon strategy, and component contracts for the core atoms. Emits tokens in the project's stack format (shadcn HSL vars or Tailwind v4 @theme). Load when the user asks to build a design system, generate design tokens, create a DESIGN.md, set up a theme, design a color or type system, pick icons, or when frontend-design routes here. Replaces design-tokens-craft and icon-craft. Sub-skill of frontend-design. Reads DIRECTION.md first.

日本語の概要は準備中です。原文の説明を表示しています。

Apply validated research paper insights to the current project codebase — improving architecture, code patterns, testing strategies, documentation, or workflows based on empirical findings. Load when learn-from-paper routes insights to the current project, or when the user asks to apply paper findings to this project, improve this codebase with research, use this paper to improve my project, or apply research to my code. Also triggers on "apply this to my project", "how can this paper help my codebase", "use these findings here", "implement paper recommendations", "use research to improve my code". Always called AFTER learn-from-paper has completed credibility and security checks — never ingests papers directly.

日本語の概要は準備中です。原文の説明を表示しています。

Repair and verify cross-references between SKILL.md files after a skill is created, renamed, removed, or restructured. Ensures every skill that calls another skill references the correct name, and every skill that is called has accurate "Called by" context. Load after universal-skill-creator creates a skill, after improve-skills completes a cycle, after a skill is renamed or removed, or when the user asks to fix cross-references, sync skill links, repair broken skill references, update skill cross-links, check skill references, or "are cross-links correct".

日本語の概要は準備中です。原文の説明を表示しています。

Turn assumptions, funnel opportunities, and product questions into a prioritised, feasibility-checked experiment backlog. Filters by traffic reality, metric latency, and method feasibility — not just ICE/RICE scoring. Maintains a living portfolio with status (idea → designed → running → readout → archived). Load when the user says "what should we test next", "build an experiment backlog", "prioritise our tests", "where should we experiment", "what's worth testing", or when the experimentation orchestrator routes here.

日本語の概要は準備中です。原文の説明を表示しています。

Translate an approved experiment spec into a launch runbook — platform binding (PostHog primary), feature flag setup, assignment unit, exposure event definition, instrumentation QA, dashboard wiring, ramp plan, monitoring, and rollback procedure. Platform-agnostic core with one strong PostHog adapter shipped; GrowthBook, Statsig, LaunchDarkly, Optimizely, and Eppo documented as a single mapping table the user adapts. Load when a spec is approved and ready to launch, or when the user says "set up the experiment", "wire this up in PostHog", "implement the test", "create the runbook", "launch checklist for this test", or when the experimentation orchestrator routes here.

日本語の概要は準備中です。原文の説明を表示しています。

Analyse experiment results, run validity checks (SRM, exposure parity, data integrity, novelty/primacy), interpret causally, make a ship/iterate/kill decision against the pre-declared rule, and append to cumulative learnings. Forces honest readouts — strips significance claims from underpowered or peek-violating tests; never lets directional results masquerade as causal wins. Load when results exist, or when the user says "read out this experiment", "analyse the test", "did the test win", "interpret the results", "what did we learn", "ship or kill", or when the experimentation orchestrator routes here.

日本語の概要は準備中です。原文の説明を表示しています。

Monitor a pull request through review and CI until it's green: verify every bot claim against the code, fix what's real, push back on what's wrong, rerun flaky checks. Use when the user asks to babysit, monitor, watch, or shepherd a PR, says "get this PR green" or "handle the review comments". Accepts an optional PR number/URL; defaults to the current branch's open PR.

日本語の概要は準備中です。原文の説明を表示しています。

Verify a code change end-to-end in the current worktree: identify what changed, run the relevant tests, get the app running, drive a browser over the affected areas, and report a verdict with screenshots. Generic across project types (Laravel/Herd, Node/bun, frontend, CLI, library). Use when the user wants to verify/QA/smoke-test a change, check that a PR or branch works, validate uncommitted work, or says "/flow", "verify this change", "does this PR work", "test and click through this". Optional target: PR number/URL, branch/ref, or worktree path; default is the current working changes.

日本語の概要は準備中です。原文の説明を表示しています。

Audit UI, docs, or prose for AI-generated tells in design and copy, then fix approved findings. Use when the user says de-slop, slop check, "looks AI-generated", or wants copy humanized.

日本語の概要は準備中です。原文の説明を表示しています。

Write and debug spreadsheet formulas (Excel/Google Sheets), pivot tables, and array formulas; translate between dialects; use when users need working formulas with examples and edge-case checks.

日本語の概要は準備中です。原文の説明を表示しています。

Automated PR review and CI auto-fix for GitHub and GitLab using the Composio CLI. Pulls diffs, fetches failing job logs, posts review comments, and loops fix commits until checks go green.

日本語の概要は準備中です。原文の説明を表示しています。

Run end-to-end deploy pipelines across Stripe, Supabase, and Vercel using the Composio CLI. Promote Stripe products, push Supabase migrations, ship Vercel deployments, and verify with post-deploy checks — all from one script.

日本語の概要は準備中です。原文の説明を表示しています。

Interact with DeerFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents in DeerFlow, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks to DeerFlow. Also use when the user mentions deerflow, deer flow, or wants to run a deep research task that DeerFlow can handle.

日本語の概要は準備中です。原文の説明を表示しています。