“markdown”的搜索结果

Create, revise, or audit AGENTS.md files from repository evidence, verified commands, and correctly scoped instructions without overwriting maintainer intent.

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Create custom AI subagents with proper plugin structure, persona generation, and companion routing skills.

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Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.

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Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.

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Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

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A hybrid memory system that provides persistent, searchable knowledge management for AI agents.

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Admin account register: system, main and backup admin, seats, plan, 2FA, shared logins and access-review dates, as CSV, SQL, JSON Schema or Notion on request. Use for access reviews.

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Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.

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Dashboard metric register: metric, source module, formula, period, value, target, trend, owner and last-updated, as CSV, SQL, JSON Schema or Notion on request. Use for KPI dashboards.

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Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.

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Access matrix of role-by-module permissions, with per-role scope, confidentiality level and SME tier, as CSV, SQL, JSON Schema or Notion on request. Use for access reviews.

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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

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360 feedback register: reviewer, subject, review cycle, visibility, due date and score, as CSV, SQL, JSON Schema or Notion on request. Use for 360 reviews or peer feedback cycles.

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When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement.

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Render Markdown, HTML, or PDF paid-advertising reports from a validated Claude Ads JSON run bundle. Use for ads report, client report, audit PDF, executive audience reporting, or exporting prior audit and plan results.

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Senior PM agent with 6 knowledge domains, 30+ frameworks, 12 templates, and 32 SaaS metrics with formulas. Pure Markdown, zero scripts.

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Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.

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Captures web sources and compiles deterministic Markdown reference bundles with metadata and checksums. Use when asked to capture URLs, research web links, bundle search results, or archive web pages into an LLM-ready reference document.

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Create professional, visually excellent presentation slides in Marp Markdown format. Use this skill when the user asks to: - Create a presentation, slides, deck, slideshow, or プレゼン / スライド - Write or generate slides about a specific topic - Make a Marp .md file for presenting Produces complete, ready-to-render .md files with embedded custom CSS theme, narrative structure, and polished visual design. Supports Japanese and English content.

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Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

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Cross-session progress tracking, pattern extraction, and session resumption. Gives agents memory across sessions using markdown files in `.memory/pipeline/progress/`. Subsumes self-improving-agent — handles both implementation tracking AND experiential learning in one skill. Workflows invoke specific protocols by name.

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Create Kotlin Compose design tokens from one of three supported sources — Google Stitch (MCP), Figma (MCP or JSON), or Codex Design (kta-design-spec output, Codex HTML/markdown artifacts). Three-layer architecture (Primitive/Semantic/Component) with code generation. Use when user asks to "generate design tokens", "create theme from Figma/Stitch/Codex design", "build Compose tokens from design spec", or "convert design source to tokens". Refuses any other input source and asks user for correct seed data.

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Per-screen design spec generator for AI design tools (Stitch / Figma AI / Codex artifacts). Consumes per-feature PRDs from kta-prd-pipeline. Emits tool-agnostic markdown specs. Triggers — design spec, AI design prompt, screen mockup brief, Figma AI input, Stitch prompt, design system tokens, post-PRD design phase, generate design specs, design brief, mockup spec. DOES NOT generate Compose code, Kotlin code, or @Preview stubs.

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Create Kotlin Compose design tokens from one of three supported sources — Google Stitch (MCP), Figma (MCP or JSON), or Claude Design (kta-design-spec output, Claude HTML/markdown artifacts). Three-layer architecture (Primitive/Semantic/Component) with code generation. Use when user asks to "generate design tokens", "create theme from Figma/Stitch/Claude design", "build Compose tokens from design spec", or "convert design source to tokens". Refuses any other input source and asks user for correct seed data.

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