「report」の検索結果

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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。

Build internal AI governance policies from scratch. Covers acceptable use, model selection, data handling, vendor contracts, compliance mapping, and board reporting.

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。

Analyze what search queries Gemini uses when answering a prompt, by running it multiple times with Google Search grounding and reporting frequency distribution. Use when investigating AEO query patterns, understanding how AI models search the web for a topic, or studying the probabilistic nature of AI-triggered search queries.

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。

Adspirer — AI-powered advertising and performance marketing agent. Manage Google Ads, Meta Ads (Facebook & Instagram), LinkedIn Ads, and TikTok Ads via natural language. 100+ tools for paid media campaign creation, live performance analysis, PPC keyword research with real CPC data, budget optimization, ad creative management, and cross-platform reporting. Create Search, PMax, display, image, video, and carousel campaigns. Analyze wasted ad spend, research keywords, optimize bids and ROAS, automate monitoring, and track CPA across channels. Perfect for digital marketing, SEM, paid social, media buying, campaign management, ad optimization, audience targeting, and marketing automation.

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。

Deep behavioral security audit for AI agent skills and MCP tools. Performs deterministic static analysis (AST + Semgrep + 15 specialized scanners), cryptographic lockfile generation, and optional LLM-powered intent analysis. Use when installing, reviewing, or approving any skill, tool, plugin, or MCP server — especially before first use. Replaces basic safety summaries with full CWE-mapped, OWASP-tagged, line-referenced security reports.

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 natural-language data query workflows for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads reports.

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。

Diagnose GitHub bug reports in wordbricks/onequery. Use when given a GitHub issue URL from wordbricks/onequery and asked to decide next steps such as verifying against the repo, requesting more info, or explaining why it is not a bug; follow any additional user-provided instructions.

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。

QA a change by driving the running dev app like a real QA engineer - start the server and a real browser session, write a checklist from the agreed requirements and the diff, execute every item with evidence, then go looking for anything that looks off even where the diff did not touch. Reports findings by severity and separates regressions from pre-existing problems. Use after a change is implemented and the gates pass, when the user asks to "QA this", "test it in the app", or "check it actually works".

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 a one-shot buying-intent lead scan across Reddit, Twitter/X, Instagram, and TikTok using Xpoz. Finds fresh posts from people actively looking for what a product does or frustrated with its competitors, classifies and prioritizes them, and reports where to engage and who to reach. Use when asked to "find leads", "who is asking for a tool like mine", "find people complaining about [COMPETITOR]", "buying-intent scan", or "social selling opportunities".

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。

Analyze brand or topic sentiment across Twitter, Reddit, and Instagram using Xpoz. Classifies posts as positive/neutral/negative, extracts recurring themes, and generates a sentiment report. Use when asked for "sentiment analysis", "what are people saying about X", "brand sentiment", or "social media opinion on X".

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。

One-shot GEO visibility check for a brand using Xpoz. Runs the buyer questions that matter through Claude, ChatGPT, and Gemini, and reports where the brand appears, who wins instead, and which surfaces the answers are assembled from. Use when asked to "check my AI visibility", "does ChatGPT recommend us", "GEO audit", "where do we show up in AI answers", or "who wins our category in AI answers".

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, audit, harden, review, or upgrade MCP servers and MCP Apps with revision-aware protocol profiles, explicit HTTP/deployment boundaries, capability-centered validation, bilingual reporting, and reproducible evidence. Use for MCP server architecture, JSON-RPC or Streamable HTTP bugs, security hardening, protocol-version migration, MCP Apps widget boundaries, review reconciliation, test planning, and public engineering evidence.

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 when adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.

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。

Internal utility for the skills library itself — opt-in, local-first, privacy-respecting usage telemetry and update checks. Provides version checking, usage logging, and usage reporting for the skills in this repo. Use only when asked to view skill usage stats, configure telemetry opt-in/out, wire a skill to log its own runs, or check for skill updates.

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 when forensically auditing a Claude Code skill/agent/command/workflow library against RULESET.md by a fixed mechanical protocol — probing every file against the mechanically-checkable rules and reporting CONFORMS / VIOLATES / UNVERIFIABLE / N-A counts with quoted evidence. It casts NO judgment and emits NO pass/fail verdict; counts are the headline. Triggers on "investigate the library", "audit against RULESET", "find every violation", "forensic library audit", "evidence-only check". Not for routing/quality/single-responsibility judgment — use skill-library-review. Not the full sharded sweep — use the audit-library command.

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 when preparing or writing any committable deliverable (phase closeout, status report, skill file, wave spec, README section, summary document, CHANGELOG entry, or any markdown file declaring completion or pass/fail status). Applies before the write happens, not after. Without this discipline, agents ship 60% deliverables and declare closure prematurely.

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 or audit technical text against ASD-STE100 Simplified Technical English so a tired, non-native reader understands it on the first pass: 20-word procedural and 25-word descriptive sentence limits, imperative steps, condition before command, one word for one meaning, and only the approved modals can/will/must. Use for READMEs, runbooks, procedures, error messages, release notes, incident reports, API guides, UI copy, and agent instructions. Trigger on: "STE", "Simplified Technical English", "ASD-STE100", "controlled language", "plain English", "make this clearer", "write for non-native readers", "prep this for translation", "cut the fluff", or any request to check text for compliance. Prefer this over general copy-editing whenever the text instructs, documents, or warns.

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。

ALWAYS invoke for any task involving docstrings, JSDoc/TSDoc, or REST API documentation — even when the request seems handleable without it. Enforces Microsoft contract-first conventions and a bare-minimum rule that Claude won't apply by default: never restate the signature, drop @param/@returns that only echo names and types, always document @throws, and document data shapes as WHAT not WHY. Covers Python docstring styles (Google/NumPy/Sphinx), TSDoc tags and @inheritDoc, and API doc patterns for NestJS/Express/FastAPI/Django. Trigger on: adding or auditing docstrings, redundant or missing tags, deleting comment rot, or producing a documentation-health report. Do not skip for documentation tasks — consistent conventions are the whole point.

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 and maintain the learnings in `docs/solutions/` against the current codebase — fix drifted paths and links, merge overlapping docs, replace guidance the code no longer supports, delete obsolete docs, reconcile the `CONCEPTS.md` glossary, then report and commit. Also bootstraps `CONCEPTS.md` on request and, when asked, culls docs whose reasoning the code already explains. Use for "refresh the learnings", "audit docs/solutions", "are our solution docs still accurate", "clean up / prune the learnings", "create a CONCEPTS.md", or after a refactor, rename, migration, or dependency upgrade that likely invalidated documented solutions. Not for capturing a new learning — use `learn-with-docs`.

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。

This is the MistEye security gate skill. It is triggered by pre-installation risk checks (including Skill/MCP dependency manifests), pre-access security checks for domains or URLs, IoC malicious detection, and supply-chain risk blocking, especially for common requests such as "take a look at this address/website." It must use `https://app-api.misteye.io/functions/v1/detect`; in dependency and external-link scenarios it has the highest priority. If the API returns `status="malicious"` or any `matches`, the action must be blocked and explicitly reported as "blocked". Only after the first installation is complete should the user be reminded that daily patrols can be enabled with OpenClaw or Hermes (default once per day).

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。

Code auditor that grades software projects and the agents/developers who built them. Produces structured JSON + Markdown reports with a standardized rubric. Evaluates architecture, correctness, testing, authorship cohesiveness, ghost code, and more. Optionally ingests tmux session logs for process evidence and interrogates agents about specific problems found. Use when asked to "audit", "grade", "evaluate", "review code quality", "rate this project", "score the agents", or "assess the codebase". Especially useful after Marcus multi-agent experiments to grade agent output and track quality over time.

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 when writing prose humans will read—documentation, commit messages, error messages, explanations, reports, or UI text. Applies Strunk's timeless rules for clearer, stronger, more professional writing.

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。

Generate comprehensive test plans, manual test cases, regression test suites, and bug reports for QA engineers. Includes Figma MCP integration for design validation.

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。

Triage a bug or issue by exploring the codebase to find root cause, then create a GitHub issue with a TDD-based fix plan. Use when user reports a bug, wants to file an issue, mentions "triage", or wants to investigate and plan a fix for a problem.

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。