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Agent Skills 排行榜 · 关键词 + 语义搜索
| # | Skill | 仓库 | 描述 | 安装量 |
|---|---|---|---|---|
| 9251 | agent-development | jezweb/claude-skills |
Agent Development for Claude Code Plugins Overview Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Understanding agent structure, triggering conditions, and system prompt design enables creating powerful autonomous capabilities. Key concepts: Agents are FOR autonomous work, commands are FOR user-initiated actions Markdown file format with YAML frontmatter Triggering via description field with examples System prompt defines agent behavior Model and color cu...
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| 9252 | image-gen | jezweb/claude-skills |
When to Use User wants to generate an AI image from a text description User says "generate image", "draw", "create picture", "配图" User says "生成图片", "画一张", "AI图" User needs a cover image, illustration, or concept art When NOT to Use User wants to create audio content (use /podcast , /speech ) User wants to create a video (use /explainer ) User wants to edit an existing image (not supported) User wants to extract content from a URL (use /content-parser ) Purpose Generate AI images using the Listen...
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| 9253 | shapely-compute | parcadei/continuous-claude-v3 |
Computational Geometry with Shapely When to Use Creating geometric shapes (points, lines, polygons) Boolean operations (intersection, union, difference) Spatial predicates (contains, intersects, within) Measurements (area, length, distance, centroid) Geometry transformations (translate, rotate, scale) Validating and fixing invalid geometries Quick Reference I want to... Command Example Create geometry create create polygon --coords "0,0 1,0 1,1 0,1" Intersection op intersection op intersection -...
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| 9254 | status | neolabhq/context-engineering-kit |
Check Research Status Run ID: $ARGUMENTS parallel-cli research status " $ARGUMENTS " --json If CLI not found, tell user to run /parallel:setup .
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| 9255 | linkedin-writer | ognjengt/founder-skills |
LinkedIn Writer Purpose Generate 2 viral LinkedIn posts in different proven formats, matched to the founder's voice, using battle-tested templates and patterns that drive engagement on LinkedIn. Execution Logic Check $ARGUMENTS first to determine execution mode: If $ARGUMENTS is empty or not provided: Respond with: "linkedin-writer loaded, proceed with your topic or idea" Then wait for the user to provide their requirements in the next message. If $ARGUMENTS contains content: Proceed immediately...
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| 9256 | auth | adobe/skills |
AEM Config Service Authentication This skill handles browser-based authentication for AEM Edge Delivery Services Config Service API using Playwright CLI. It opens a browser window for Adobe ID login and captures the auth token when the browser is closed. When to Use This Skill Before generating admin/authoring/development guides that need API data When Config Service API returns 401 Unauthorized User says "login", "authenticate", "get auth token" Orchestrated by handover/admin/authoring/developm...
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| 9257 | competitive-intel | alirezarezvani/claude-skills |
Competitive Intelligence Systematic competitor tracking. Not obsession — intelligence that drives real decisions. Keywords competitive intelligence, competitor analysis, battlecard, win/loss analysis, competitive positioning, competitive tracking, market intelligence, competitor research, SWOT, competitive map, feature gap analysis, competitive strategy Quick Start /ci:landscape — Map your competitive space (direct, indirect, future) /ci:battlecard [name] — Build a sales battlecard for a...
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| 9258 | scikit-learn-best-practices | mindrally/skills |
Scikit-learn Best Practices Expert guidelines for scikit-learn development, focusing on machine learning workflows, model development, evaluation, and best practices. Code Style and Structure Write concise, technical responses with accurate Python examples Prioritize reproducibility in machine learning workflows Use functional programming for data pipelines Use object-oriented programming for custom estimators Prefer vectorized operations over explicit loops Follow PEP 8 style guidelines Machi...
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| 9259 | shadcn | vercel-labs/vercel-plugin |
shadcn/ui A framework for building ui, components and design systems. Components are added as source code to the user's project via the CLI. IMPORTANT: Run all CLI commands using the project's package runner: npx shadcn@latest , pnpm dlx shadcn@latest , or bunx --bun shadcn@latest — based on the project's packageManager . Examples below use npx shadcn@latest but substitute the correct runner for the project. Current Project Context !`npx shadcn@latest info --json 2 >/dev/ null || echo ' { "error...
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| 9260 | debugging-streamlit | streamlit/streamlit |
Debugging Streamlit Apps Quick Start make debug my_app.py This starts both backend (Streamlit/Python) and frontend (Vite/React) with hot-reload. The app URL is printed on startup (default http://localhost:3001 ; 3000 is reserved for manual make frontend-dev ; it may use 3002+ if other debug sessions are running). Avoid pinning VITE_PORT unless you have a specific hard requirement (last resort). Hot-reload behavior: Frontend : Changes to frontend/ code are applied within seconds. Backend : Only c...
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| 9261 | cloudflare-troubleshooting | daymade/claude-code-skills |
Cloudflare Troubleshooting Core Principle Investigate with evidence, not assumptions. Always query Cloudflare API to examine actual configuration before diagnosing issues. The skill's value is the systematic investigation methodology, not predetermined solutions. Investigation Methodology 1. Gather Credentials Request from user: Domain name Cloudflare account email Cloudflare Global API Key (or API Token) Global API Key location: Cloudflare Dashboard → My Profile → API Tokens → View Global ...
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| 9262 | sympy | davila7/claude-code-templates |
SymPy - Symbolic Mathematics in Python Overview SymPy is a Python library for symbolic mathematics that enables exact computation using mathematical symbols rather than numerical approximations. This skill provides comprehensive guidance for performing symbolic algebra, calculus, linear algebra, equation solving, physics calculations, and code generation using SymPy. When to Use This Skill Use this skill when: Solving equations symbolically (algebraic, differential, systems of equations) Per...
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| 9263 | firebase | davila7/claude-code-templates |
Firebase You're a developer who has shipped dozens of Firebase projects. You've seen the "easy" path lead to security breaches, runaway costs, and impossible migrations. You know Firebase is powerful, but you also know its sharp edges. Your hard-won lessons: The team that skipped security rules got pwned. The team that designed Firestore like SQL couldn't query their data. The team that attached listeners to large collections got a $10k bill. You've learned from all of them. You advocate for ...
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| 9264 | codebase-cleanup-deps-audit | sickn33/antigravity-awesome-skills |
Dependency Audit and Security Analysis You are a dependency security expert specializing in vulnerability scanning, license compliance, and supply chain security. Analyze project dependencies for known vulnerabilities, licensing issues, outdated packages, and provide actionable remediation strategies. Use this skill when Auditing dependencies for vulnerabilities Checking license compliance or supply-chain risks Identifying outdated packages and upgrade paths Preparing security reports or remedia...
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| 9265 | recall | parcadei/continuous-claude-v3 |
/recall — Search Past Claude & Codex Sessions Search all past Claude Code and Codex sessions using full-text search with BM25 ranking. Usage python3 ~/.claude/skills/recall/scripts/recall.py QUERY [ --project PATH ] [ --days N ] [ --source claude | codex ] [ --limit N ] [ --reindex ] Examples Simple keyword search python3 ~/.claude/skills/recall/scripts/recall.py "bufferStore" Phrase search (exact match) python3 ~/.claude/skills/recall/scripts/recall.py '"ACP protocol"' Boolean query python3 ...
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| 9266 | environment-triage | parcadei/continuous-claude-v3 |
Environment Triage When uv sync or pip install behaves unexpectedly, check the actual interpreter. Pattern System Python is not authoritative if uv/venv selects a different interpreter. DO What uv ACTUALLY uses uv run python --version What's pinned (this controls uv) cat .python-version Confirm package is installed uv pip show <package> Confirm import works in uv context uv run python -c "import <package>; print(<package>.__version__)" Common Fix If optional deps require Python 3.12...
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| 9267 | implement_plan_micro | parcadei/continuous-claude-v3 |
Formal Specification Multimodal Logic Integration Five modal logics via fusion with bridge principles: JL: Justification Logic - evidence-backed claims IEL: Inferential Erotetic Logic - question handling TEL: Temporal Epistemic Logic - phase sequencing SDL: Standard Deontic Logic - obligations/permissions DEL: Dynamic Epistemic Logic - action modalities Justification Logic (JL) Justification terms [h]:context(task_n) Handoff h justifies task context [v]:verified(phase_n) ...
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| 9268 | nansen-smart-money-tracker | nansen-ai/nansen-cli |
Smart Money All commands: nansen research smart-money <sub> [options] Subcommands Netflow — what tokens are smart money accumulating? nansen research smart-money netflow --chain solana --limit 10 DEX trades — real-time spot trades by smart money nansen research smart-money dex-trades --chain solana --labels "Smart Trader" --limit 20 Holdings — aggregated SM portfolio nansen research smart-money holdings --chain solana --limit 10 Perp trades — Hyperliquid only (no --chain needed) nansen resea...
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| 9269 | dial-your-context | sanity-io/agent-context |
Dial Your Context Help a user create the Instructions field content for their Sanity Agent Context MCP. The goal is a concise set of pure deltas — only information the agent can't figure out from the auto-generated schema. What you're building The Agent Context MCP already provides the agent with: A compressed schema of all document types and fields A GROQ query tutorial (~194 lines) Response style guidance Tool descriptions for GROQ queries, semantic search, etc. The Instructions field you're c...
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| 9270 | feature engineering | aj-geddes/useful-ai-prompts |
Feature Engineering Overview Feature engineering creates and transforms features to improve model performance, interpretability, and generalization through domain knowledge and mathematical transformations. When to Use When you need to improve model performance beyond using raw features When dealing with categorical variables that need encoding for ML algorithms When features have different scales and require normalization When creating domain-specific features based on business knowledge When h...
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| 9271 | agentica-prompts | parcadei/continuous-claude-v3 |
Agentica Prompt Engineering Write prompts that Agentica agents reliably follow. Standard natural language prompts fail ~35% of the time due to LLM instruction ambiguity. The Orchestration Pattern Proven workflow for context-preserving agent orchestration: 1. RESEARCH (Nia) → Output to .claude/cache/agents/research/ ↓ 2. PLAN (RP-CLI) → Reads research, outputs .claude/cache/agents/plan/ ↓ 3. VALIDATE → Checks plan against best practices ↓ 4. IMPLEMENT (...
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| 9272 | fpf:status | neolabhq/context-engineering-kit |
Status Check Display the current state of the FPF knowledge base. Action (Run-Time) Check Directory Structure: Verify .fpf/ exists and contains required subdirectories. Count Hypotheses: List files in each knowledge layer: .fpf/knowledge/L0/ (Proposed) .fpf/knowledge/L1/ (Verified) .fpf/knowledge/L2/ (Validated) .fpf/knowledge/invalid/ (Rejected) Check Evidence Freshness: Scan .fpf/evidence/ for expired evidence. Count Decisions: List files in .fpf/decisions/ . Report to user. Status Report Form...
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| 9273 | cloudflare-turnstile | jezweb/claude-skills |
Cloudflare Turnstile Status: Production Ready ✅ Last Updated: 2026-01-21 Dependencies: None (optional: @marsidev/react-turnstile for React) Latest Versions: @marsidev/react-turnstile@1.4.1, turnstile-types@1.2.3 Recent Updates (2025): December 2025: @marsidev/react-turnstile v1.4.1 fixes race condition in script loading August 2025: v1.3.0 adds rerenderOnCallbackChange prop for React closure issues March 2025: Upgraded Turnstile Analytics with TopN statistics (7 dimensions: hostnames, browser...
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| 9274 | firebase-firestore-standard | firebase/skills |
Firestore Standard Edition This skill provides a complete guide for getting started with Cloud Firestore Standard Edition, including provisioning, securing, and integrating it into your application. Provisioning To set up Cloud Firestore in your Firebase project and local environment, see provisioning.md . Security Rules For guidance on writing and deploying Firestore Security Rules to protect your data, see security_rules.md . SDK Usage To learn how to use Cloud Firestore in your application co...
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| 9275 | tldr-deep | parcadei/continuous-claude-v3 |
TLDR Deep Analysis Full 5-layer analysis of a specific function. Use when debugging or deeply understanding code. Trigger /tldr-deep <function_name> "analyze function X in detail" "I need to deeply understand how Y works" Debugging complex functions Layers Layer Purpose Command L1: AST Structure tldr extract <file> L2: Call Graph Navigation tldr context <func> --depth 2 L3: CFG Complexity tldr cfg <file> <func> L4: DFG Data flow tldr dfg <file> <func> L5: Slice Dependencies tldr slice <file> <...
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| 9276 | setup-codemap-cli | neolabhq/context-engineering-kit |
User Input: $ARGUMENTS Guide for setup Codemap CLI 1. Determine setup context Ask the user where they want to store the configuration: Options: Project level (shared via git) - Configuration tracked in version control, shared with team CLAUDE.md updates go to: ./CLAUDE.md Hook settings go to: ./.claude/settings.json Show more
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| 9277 | pytorch-lightning | k-dense-ai/scientific-agent-skills |
PyTorch Lightning - High-Level Training Framework Quick start PyTorch Lightning organizes PyTorch code to eliminate boilerplate while maintaining flexibility. Installation: pip install lightning Convert PyTorch to Lightning (3 steps): import lightning as L import torch from torch import nn from torch.utils.data import DataLoader, Dataset Step 1: Define LightningModule (organize your PyTorch code) class LitModel(L.LightningModule): def __init__(self, hidden_size=128): super()....
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| 9278 | codex-ppt | ningzimu/codex-ppt-skill |
Codex PPT Overview This skill creates image-based PPT decks. Each slide is a complete 16:9 image generated with the best available image backend. The image contains the slide title, key points, and visual composition. The generated images are then assembled into a .pptx file with scripts/assemble_ppt.py . Prefer the built-in image generation and editing tool when it is available. If it is unavailable, or if the user explicitly requests API/CLI mode, use this skill's local fallback CLI at scripts...
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| 9279 | kernel-agent-browser | kernel/skills |
This skill documents best practices for using agent-browser's built-in Kernel provider (`-p kernel`) for cloud browser automation. When to Use This Skill Use this skill when you need to: - Automate websites using `agent-browser -p kernel` commands - Handle bot detection on sites with aggressive anti-bot measures - Persist login sessions across automation runs using profiles - Work with iframes including cross-origin payment forms - Get live view URLs for debugging or manual intervention ...
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| 9280 | outline-coach | jwynia/agent-skills |
Outline Coach: Assistive Structural Guidance Skill You are an outline coach. Your role is to help writers develop their own story structure through questions, diagnosis, and guided exploration. You never generate outline content for them. The Core Constraint You do not generate: Scene beats or beat sequences Character arc mappings Plot structure proposals Worldbuilding systems Pacing recommendations as specific structures Sample prose or dialogue Any structural content they could copy into t...
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| 9281 | websocket-development | mindrally/skills |
WebSocket Development You are an expert in WebSocket development and real-time communication systems. Follow these best practices when building WebSocket-based applications. Core Principles Think through the implementation step-by-step before writing code Follow the user's requirements carefully and to the letter Prioritize security, scalability, and maintainability throughout Leave NO todos, placeholders, or missing pieces in the implementation Connection Management Establishing Connections A...
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| 9282 | continuity-ledger | parcadei/continuous-claude-v3 |
Continuity Ledger Note: This skill is now an alias for /create_handoff. Both output the same YAML format. Create a YAML handoff document for state preservation across /clear. This is the same as /create_handoff. Process 1. Filepath & Metadata First, determine the session name from existing handoffs: ls -td thoughts/shared/handoffs/*/ 2>/dev/null | head -1 | xargs basename This returns the most recently modified handoff folder name (e.g., open-source-release). Use this as the handoff folde...
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| 9283 | web-development | mindrally/skills |
When to use this skill Use this skill for Web frontend project development when you need to: Develop web frontend pages and interfaces Deploy static websites to CloudBase static hosting Integrate CloudBase Web SDK for database, cloud functions, and authentication Set up modern frontend build systems (Vite, Webpack, etc.) Handle routing and build configurations for static hosting Do NOT use for: Mini-program development (use miniprogram-development skill) Backend service development (use cloudrun...
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| 9284 | pnpm | mindrally/skills |
pnpm is a fast, disk space efficient package manager. It uses a content-addressable store to deduplicate packages across all projects on a machine, saving significant disk space. pnpm enforces strict dependency resolution by default, preventing phantom dependencies. Configuration should preferably be placed in pnpm-workspace.yaml for pnpm-specific settings. Important: When working with pnpm projects, agents should check for pnpm-workspace.yaml and .npmrc files to understand workspace structure a...
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| 9285 | data-scientist | borghei/claude-skills |
Use this skill when Working on data scientist tasks or workflows Needing guidance, best practices, or checklists for data scientist Do not use this skill when The task is unrelated to data scientist You need a different domain or tool outside this scope Instructions Clarify goals, constraints, and required inputs. Apply relevant best practices and validate outcomes. Provide actionable steps and verification. If detailed examples are required, open resources/implementation-playbook.md . You are a...
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| 9286 | video-summarizer | liang121/video-summarizer |
Video Summarizer Overview Download videos from any platform and generate a complete resource package including: Original video file (mp4) Audio file (mp3) Subtitle file (with timestamps, vtt/srt format) Summary file (summary.md) Supports all 1800+ websites supported by yt-dlp. Trigger Conditions When the user: Provides a video link and asks for a summary Says "summarize this video", "what's in this video" Asks to "extract video content", "transcribe video" Says "download this video" Provides a l...
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| 9287 | agentica-claude-proxy | parcadei/continuous-claude-v3 |
Agentica-Claude Code Proxy Integration Use this skill when developing or debugging the Agentica-Claude proxy integration. When to Use Setting up Agentica agents to use Claude Code tools Debugging agent hallucination issues Fixing permission errors in file operations Understanding the REPL response format Architecture Overview Agentica Agent → S_M_BASE_URL → Claude Proxy → claude -p → Claude CLI (with tools) (localhost:2345) (localhost:8080) Critical Requirements 1. --allowe...
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| 9288 | migrate | parcadei/continuous-claude-v3 |
Migrate to Playwright Interactive migration from Cypress or Selenium to Playwright with file-by-file conversion. Input $ARGUMENTS can be: "from cypress" — migrate Cypress test suite "from selenium" — migrate Selenium/WebDriver tests A file path: convert a specific test file Empty: auto-detect source framework Steps 1. Detect Source Framework Use Explore subagent to scan: cypress/ directory or cypress.config.ts → Cypress selenium , webdriver in package.json deps → Selenium .py test files with sel...
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| 9289 | observe-before-editing | parcadei/continuous-claude-v3 |
Observe Before Editing Before editing code to fix a bug, confirm what the system actually produced. Pattern Outputs don't lie. Code might. Check outputs first. DO Check if expected directories exist: ls -la .claude/cache/ Check if expected files were created: ls -la .claude/cache/learnings/ Check logs for errors: tail .claude/cache/*.log Run the failing command manually to see actual error Only then edit code DON'T Assume "hook didn't run" without checking outputs Edit code based on what you...
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| 9290 | ffmpeg-video-editor | bryanwhl/ffmpeg-video-editor |
FFmpeg Video Editor You are a video editing assistant that translates natural language requests into FFmpeg commands. When the user asks to edit a video, generate the correct FFmpeg command. How to Generate Commands Identify the operation from the user's request Extract parameters (input file, output file, timestamps, formats, etc.) Generate the FFmpeg command using the patterns below If output filename not specified , create one based on the operation (e.g., video_trimmed.mp4 ) Always include -...
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| 9291 | text-to-image-prompt-optimizer | manzxiao/text-to-image-prompt-optimizer |
AI Image Prompt Optimizer Generate professional, optimized prompts for AI image generation tools with primary support for Google Gemini (Nano Banana) , plus Midjourney, Stable Diffusion, DALL-E, Leonardo.ai, and others. Core Workflow When a user requests prompt generation or optimization: Understand the intent Identify the core subject and desired outcome Ask clarifying questions ONLY if the request is extremely vague Default to reasonable assumptions rather than over-questioning Generate compre...
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| 9292 | project-workflow | jezweb/claude-skills |
Project Workflow Skill 9 integrated slash commands for complete project lifecycle automation: idea validation → planning → execution → session management → context preservation → release. Time savings: 35-55 minutes per project lifecycle Installation Marketplace: /plugin install project-workflow@claude-skills Manual: Copy commands/*.md to ~/.claude/commands/ The 7 Commands 1. /explore-idea - Pre-Planning Exploration Use when: Rough idea that needs tech stack validation, scope management, ...
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| 9293 | fpf:propose-hypotheses | neolabhq/context-engineering-kit |
Propose Hypotheses Workflow Execute the First Principles Framework (FPF) cycle: generate competing hypotheses, verify logic, validate evidence, audit trust, and produce a decision. User Input Problem Statement: $ARGUMENTS Workflow Execution Step 1a: Create Directory Structure (Main Agent) Create .fpf/ directory structure if it does not exist: mkdir -p .fpf/ { evidence,decisions,sessions,knowledge/ { L0,L1,L2,invalid } } touch .fpf/ { evidence,decisions,sessions,knowledge/ { L0,L1,L2,invalid } } ...
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| 9294 | fpf:decay | neolabhq/context-engineering-kit |
Evidence Freshness Management Manages evidence freshness by identifying stale decisions and providing governance actions. Implements FPF B.3.4 (Evidence Decay). Key principle: Evidence is perishable. Decisions built on expired evidence carry hidden risk. Quick Concepts What is "stale" evidence? Every piece of evidence has a valid_until date. A benchmark from 6 months ago may no longer reflect current system performance. A security audit from before a major dependency update doesn't account for n...
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| 9295 | fpf:actualize | neolabhq/context-engineering-kit |
Actualize Knowledge Base This command is a core part of maintaining a living assurance case. It keeps your FPF knowledge base ( .fpf/ ) in sync with the evolving reality of your project's codebase. The command performs a three-part audit against recent git changes to surface potential context drift, stale evidence, and outdated decisions. This aligns with the Observe phase of the FPF Canonical Evolution Loop (B.4) and helps manage Epistemic Debt (B.3.4). Action (Run-Time) Step 1: Check Git Chang...
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| 9296 | drawio-skill | agents365-ai/drawio-skill |
Draw.io Diagrams Overview Generate .drawio XML files and export to PNG/SVG/PDF/JPG locally using the native draw.io desktop app CLI. Supported formats: PNG, SVG, PDF, JPG — no browser automation needed. PNG, SVG, and PDF exports support --embed-diagram ( -e ) — the exported file contains the full diagram XML, so opening it in draw.io recovers the editable diagram. Use double extensions ( name.drawio.png ) to signal embedded XML. Bundled resources When the workflow references one of these, read i...
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| 9297 | system-overview | parcadei/continuous-claude-v3 |
System Overview Show users how Continuous Claude works - the opinionated setup with hooks, memory, and coordination. When to Use User asks "how does this work?" User asks "what can you remember?" User asks "what's different about this setup?" User runs /system_overview Response CONTINUOUS CLAUDE SYSTEM OVERVIEW ================================= MEMORY LAYER (PostgreSQL + pgvector) ------------------------------------ - 78,000+ temporal facts from past sessions - Learnings extracted automatica...
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| 9298 | tldr-stats | parcadei/continuous-claude-v3 |
TLDR Stats Skill Show a beautiful dashboard with token usage, actual API costs, TLDR savings, and hook activity. When to Use See how much TLDR is saving you in real $ terms Check total session token usage and costs Before/after comparisons of TLDR effectiveness Debug whether TLDR/hooks are being used See which model is being used Instructions IMPORTANT: Run the script AND display the output to the user. Run the stats script: python3 $CLAUDE_PROJECT_DIR/.claude/scripts/tldr_stats.py Copy the...
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| 9299 | tldr-router | parcadei/continuous-claude-v3 |
TLDR Smart Router Maps questions to the optimal tldr command. Use this to pick the right layer. Question → Command Mapping "What files/functions exist?" tldr tree . --ext .py File overview tldr structure src/ --lang python Function/class overview Use: Starting exploration, orientation "What does X call / who calls X?" tldr context <function> --project . --depth 2 tldr calls src/ Use: Understanding architecture, finding entry points "How complex is X?" tldr cfg <file> <functio...
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| 9300 | prompt-optimizer | getsentry/skills |
Prompt Optimizer Analyze a draft prompt, critique it, match it to ECC ecosystem components, and output a complete optimized prompt the user can paste and run. When to Use User says "optimize this prompt", "improve my prompt", "rewrite this prompt" User says "help me write a better prompt for..." User says "what's the best way to ask Claude Code to..." User says "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令" User pastes a draft prompt and asks for feedback or enhancement User says "I don't know ...
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