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概要と使いどころ
Use when extracting structured information from text - named entity recognition, relation extraction, coreference resolution, knowledge graph construction, and information extraction pipelinesUse when ", " mentioned.
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。
Expert in Cursor AI IDE - the leading AI-powered code editor. Covers Rules files for project-specific AI behavior, Plan Mode for structured development, Background Agents for parallel work, and advanced features like voice mode and browser integration. Essential for developers maximizing AI-assisted coding productivity. Use when "cursor ai, cursor rules, .cursorrules, cursor composer, cursor agent, plan mode, background agent, cursor tips, cursor, ide, ai-coding, editor, productivity, agent, developer-tools" mentioned.
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 whether a paper's baseline comparisons are COMPLETE, FAIR, and SIGNIFICANT: a required recent SOTA baseline is missing while 'best/SOTA' is claimed (HP-MISSING-BASELINE); a baseline is undertuned / given less compute-tuning-data, run at a mismatched config, or the equal-budget ablation-as-baseline is absent (HP-WEAK-BASELINE); 'outperforms' is asserted over overlapping error bars or with no variance/seeds (HP-SIG-OVERLAP); and a cross-row 'improves over baseline by X%' is arithmetically wrong (HP-DELTA-ERROR, cross-row form only). A versioned per-domain baseline profile + a live leaderboard/recency search are assembled by the EXECUTOR as structured facts; a fresh cross-model reviewer (gpt-5.6-sol xhigh, read-only, fresh thread per dimension) PROPOSES findings, each span-anchored to a ledger claim_id; tools/adjudicate_findings.py DECIDES the verdict. Works at L0 (stated comparisons) and deepens at L2 (configs/result files). A completeness question it cannot settle internally becomes needs_external_check, never a guessed missing baseline. Emits baseline-comparison-audit.findings.json; computes NO verdict. Detect-only. Triggers: "baseline audit", "missing baselines", "is the comparison fair", "weak baseline", "baseline 误报", "SOTA earned?".
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。
Azure.AI.DocumentIntelligence (.NET) workflow skill. Use this skill when the user needs Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Azure.AI.DocumentIntelligence (.NET) workflow skill. Use this skill when the user needs Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Apify Actorization workflow skill. Use this skill when the user needs Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Apify Actorization workflow skill. Use this skill when the user needs Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Agent-Friendly CLI Spec v0.1 workflow skill. Use this skill when the user needs Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Agent-Friendly CLI Spec v0.1 workflow skill. Use this skill when the user needs Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
ADHX - X/Twitter Post Reader workflow skill. Use this skill when the user needs Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Draft an incident postmortem with timeline, RCA, and action items. Use when a senior developer needs a structured post-incident report.
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。
Evaluate third-party vendors for engineering fit. Use when a senior developer needs a structured vendor assessment.
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。
Provide a systematic debugging checklist. Use when a junior developer is stuck and needs a structured approach.
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。
Create an onboarding guide for new engineers. Use when a senior developer needs structured onboarding materials.
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。
Draft release notes from changes and PRs. Use when a mid-level developer needs a structured changelog.
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。
Review a pull request for correctness, regressions, and missing tests. Use when a mid-level developer needs structured review guidance.
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。
Assign items to a CLOSED label vocabulary that is too large to put in a prompt — product taxonomies, category hierarchies, tag vocabularies, routing tables, ICD/SIC-style code lists. A cheap model writes the label it thinks the vocabulary would use, and an embedder snaps that writing onto the nearest legal value, so the schema is never transmitted and the output is always in-vocabulary. Use for "classify these into our taxonomy", "tag these against the existing tag list", "map these queries to categories", "the enum is too big to send", or a Literal/enum that hits a provider cap. NOT for a vocabulary that fits in a prompt — structured output measured 0.701 acc@1 there against this pattern's 0.564. NOT for open-ended labelling with no fixed vocabulary, and not for ranked retrieval over documents (bm25).
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。
Maintains a structured running-notes document during long work sessions. Use when the user says "session notes", "update notes", "start session notes", "show session notes", or when you recognize the current session has accumulated enough state (decisions, corrections, files touched, errors) that it risks being lost under context pressure. Stores notes as a procedure memory tagged [session-memory, active] so they survive container death within the same session thread.
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。
Maintain a structured task list for the current session. Use proactively when a request requires 3+ distinct steps, the user provides multiple items, or complex work benefits from explicit progress tracking. Storage persists via Muninn config across container death. Adapted from Claude Code's TodoWrite tool.
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。
Break out of a locked problem frame by picking one disciplined move — reframe, provocation (Po), random stimulus, SCAMPER, inversion, structured analogy, constraint play, or family traversal — and committing to it before evaluating. Use when stuck, when options feel narrow or obvious, when iterations produce variations of the same idea, or when the user says "widen this", "break out of", "think differently", "I'm stuck", "feels too obvious", "stress-test the framing", "what am I missing", or holds two related examples and asks what lies between or beyond them. Complements challenging (which evaluates) and convening-experts (which synthesizes viewpoints); this skill generates distance, not judgment.
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。
Use this skill when the user explicitly asks for TDD or a tests-first workflow, or when developing a new feature with a test coverage requirement. Provides a structured red-green-refactor workflow with unit, integration, and E2E test guidance.
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。
Structured code review through the shared OpenClaw agent-skills installation.
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。
Route HugeGraph MCP graph data extraction and controlled import/delete tasks to stable public tools. Use when the user asks to extract graph data from text, import structured vertices or edges, verify an import, or asks whether table, SQL, update, or delete graph writes are available.
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。
Route HugeGraph MCP structured graph query tasks to stable read-only tools. Use when the user asks graph questions, asks to generate Gremlin, provides Gremlin to explain, or needs read-only graph exploration.
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。