Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
45,431 skills from 2,188 repositories · updated 56 seconds ago
45,429 skills
- add-webexnanocoai/nanoclawAdd Webex channel integration via Chat SDK.OtherNo warnings★ 31K↓ —
- customizenanocoai/nanoclawAdd new capabilities or modify NanoClaw behavior. Use when user wants to add channels (Telegram, Slack, email input), change triggers, add integrations, modify the router, or make any other customizations. This is an interactive skill that asks questions to understand what the user wants.ProductivityNo warnings★ 31K↓ —
- skill-feedback-writertopoteretes/cogneeUse to identify missing instructions in another skill based on its output.WritingNo warnings★ 32.7K↓ —
- pr-comment-evaluatortopoteretes/cogneeUse to judge whether a PR review comment sounds polite.EngineeringNo warnings★ 32.7K↓ —
- diff-risk-explainertopoteretes/cogneeUse to briefly explain small code diffs.EngineeringNo warnings★ 32.7K↓ —
- hf-cloud-sagemaker-deployment-plannerhuggingface/skillsPlan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.OfficialDevOpsNo warnings★ 11.2K↓ —
- cognee-custom-graph-modelstopoteretes/cogneeUse when defining the shape of cognee's knowledge graph with graph_model= — writing DataPoint node classes, choosing identity and index fields so nodes merge and are searchable, declaring typed Edge fields and FromIdentity references, building a model from a JSON schema, or debugging duplicated nodes, missing edges, or InvalidReferenceTypeError.WritingNo warnings★ 32.7K↓ —
- company-brain-company-qatopoteretes/cogneeBuild one company memory from a SQL database, a support ticket export and a folder of documents, linked into one graph by cognee, then answer questions that need several of those sources together. Use when someone wants to connect their company's database, tickets and docs, or asks who owns, decided or is handling something across them. Runs locally; reads the sources, writes only to cognee's memory.TestingNo warnings★ 32.7K↓ —
- cognee-improve-sessionstopoteretes/cogneeUse when working with cognee's session memory or improve() — storing conversation turns, agent traces and feedback with session_id, bridging sessions into the permanent graph, reading an ImproveResult, understanding why an improve stage was skipped, already_completed or lock_held, or tuning the IMPROVE_* settings.ProductivityNo warnings★ 32.7K↓ —
- cognee-custom-pipelinestopoteretes/cogneeUse when building your own cognee processing — writing custom tasks, chaining them into a pipeline with run_custom_pipeline or the lightweight run_pipeline (from cognee.pipelines import run_pipeline), storing custom DataPoints with add_data_points, running custom enrichment over the existing graph, checking pipeline run status, or debugging how data flows between tasks (batch_size, data_per_batch, ctx, Drop, enriches).WritingNo warnings★ 32.7K↓ —
- self-hosted-companiontopoteretes/cogneeChat with a companion that knows your notes folder (a journal, an Obsidian vault, any .md or .txt files) and every earlier chat, using cognee memory with local databases. Use when someone wants to ask questions about their own notes, or to talk with a companion that remembers past conversations. Runs locally; reads the notes folder, writes only to cognee's memory.WritingNo warnings★ 32.7K↓ —
- cognee-integrationstopoteretes/cogneeUse when the user wants to connect cognee to external services — switching LLM or embedding providers (OpenAI, Azure, Gemini, Anthropic, Ollama, OpenRouter), changing databases (Postgres, PGVector, Neo4j, Neptune, Turso), S3 storage, or the MCP server for IDE integration.DevOpsNo warnings★ 32.7K↓ —
- personalized-emailtopoteretes/cogneeDraft a reply to your newest Gmail email that knows what you discussed in your Granola meetings, what you promised the sender, and how you write, using cognee memory. Use when someone asks to answer or reply to their latest email in their own tone. Runs locally; reads Gmail read-only; the draft is printed, never sent.ProductivityNo warnings★ 32.7K↓ —
- huggingface-datasetshuggingface/skillsUse this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.OfficialEngineeringNo warnings★ 11.2K↓ —
- huggingface-zerogpuhuggingface/skillsAI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.OfficialWritingNo warnings★ 11.2K↓ —
- cognee-performancetopoteretes/cogneeUse when cognee is slow, expensive, or hitting rate limits — speeding up or throttling ingestion (remember/cognify batching, chunk size, LLM and embedding rate limits, per-stage models), cutting read latency, estimating cost before ingesting, running work in the background, or planning how to scale a deployment.DevOpsNo warnings★ 32.7K↓ —
- gws-keepgoogleworkspace/cliManage Google Keep notes.ProductivityNo warnings★ 31.8K↓ —
- cognee-migrationstopoteretes/cogneeUse when dealing with cognee database migrations — understanding when they run automatically, checking or repairing migration state with cognee-cli upgrade/downgrade/stamp/current, a write blocked by a failed migration, authoring a new Alembic (relational schema) revision or a graph/vector data migration, or moving data between systems (relational DB import, memory export/import).DataNo warnings★ 32.7K↓ —
- cognee-communitytopoteretes/cogneeUse when the user needs something that ships outside cognee core — community database adapters (Qdrant, Milvus, Weaviate, Redis, Pinecone, FalkorDB, Memgraph, DuckDB, NetworkX, …), data-source connectors (Slack, Gmail, Notion, Confluence, Google Drive), custom tasks/pipelines/retrievers (Exa, ScrapeGraph, codify), Keywords AI observability — or wants to contribute a package to the cognee-community repo.DevOpsNo warnings★ 32.7K↓ —
- cognee-installtopoteretes/cogneeUse when the user wants to install cognee and run their first remember → recall flow with the Python SDK — fresh setup, virtual env, extras selection, or a minimal working example.EngineeringNo warnings★ 32.7K↓ —
- cognee-servertopoteretes/cogneeUse when the user wants to run the cognee API server (and optional UI) on their own machine — starting it, checking it's healthy, connecting the SDK or other clients to it, and choosing the right auth posture.DesignNo warnings★ 32.7K↓ —
- cognee-forgettopoteretes/cogneeUse when removing data from cognee memory with forget() in the SDK, HTTP API, or CLI — finding which dataset and document hold the content to delete (listing datasets and data items, reading raw content), choosing between deleting one document, a whole dataset, or only the graph/vector memory, and doing it safely.EngineeringNo warnings★ 32.7K↓ —
- cognee-dockertopoteretes/cogneeUse when the user wants to run cognee with Docker or docker compose — trying it out from the prebuilt image, starting the API server in a container, or bringing up the full stack (UI, MCP, Postgres, Neo4j) with compose profiles.DevOpsNo warnings★ 32.7K↓ —
- business-name-fitalirezarezvani/claude-skillsSuggest, pick, or vet a business, startup, or product name that stays true to the founder's cultural origin while working professionally in the markets they want to sell into. Use when someone is naming a company, brand, or product and cares about how it lands across languages and regions — for example a name that sounds right at home but might read oddly to English speakers, or an authentic name they want to check before committing. Trigger this for any request about choosing a business name, checking if a name "works" abroad, spotting bad meanings in other languages, or making a name sound trustworthy in a specific market — even if the person doesn't say the word "skill".PlanningNo warnings★ 28.6K↓ —
intended-vs-implemented
phuryn/pm-skills
EngineeringUpdated Oct 16, 2026
From the author
The method for finding the gap between what a system is supposed to do and what the code actually does — the class of bug generic scanners miss because they have no model of intent. Defines what counts as documented intent, what counts as implementation evidence, which mismatches matter, and how to avoid hand-wavy findings. Use when auditing AI-built code, reviewing access control against documented permissions, or checking whether a codebase matches its own documentation.
Install
npx skills add phuryn/pm-skills --skill intended-vs-implemented -a claude-code
Installs to .claude/skills/intended-vs-implemented/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Instructions onlyNo network use seenLicence: MIT
Safety checks on SKILL.md
No warnings.
Why 94
Security100
Provenance93
Maintenance100
Licence100
Adoption69
Files (1)
- SKILL.md