Skills
Packaged SKILL.md capabilities that extend Claude with on-demand expertise.
Skills are packaged capabilities Claude loads on demand. Each is a SKILL.md file — optionally bundled with scripts and resources — that Claude reads only when it's relevant, via progressive disclosure, so it adds expertise without permanently filling your context window.
33 results
LLM Output Schema Generator
Turn an example of the data you want from an LLM into a precise, validated output schema (Pydantic / Zod / JSON Schema) and wire it into structured-output calls. Use when adding typed LLM output, replacing brittle JSON parsing, or designing an extraction shape.
MCP Server Scaffolder
Scaffold a new Model Context Protocol (MCP) server from a description — pick the SDK and transport, generate a typed first tool with a strict schema, and wire up MCP Inspector testing and the client-registration command. Use when starting a new MCP server and you want a correct, runnable skeleton instead of copying a README.
Provider Fallback Wrapper
Wrap LLM calls so a provider outage, rate limit, or timeout degrades gracefully — with multi-provider fallback, bounded retries with backoff, and timeouts. Use when an app depends on a single model/provider and needs production resilience.
Tool Definition Generator
Generate clean function/tool schemas for an LLM agent from existing code or a spec — accurate JSON Schema, model-facing descriptions, honest required fields, and enums that make invalid calls impossible. Use when wiring functions into an agent's tool-calling loop.
Chunking Strategy Optimizer
Find the chunking strategy and size that maximizes retrieval quality for a specific corpus, by sweeping configurations against a fixed eval set instead of guessing. Use when RAG answers miss obvious content, when standing up a new corpus, or when picking chunk size/overlap.
Embedding Set Inspector
Diagnose the health of an embedding set before blaming the retriever — checking normalization, dimensionality, near-duplicates, degenerate vectors, and corpus/query distribution mismatch. Use when retrieval quality is poor, after a re-embed, or before shipping a new index.
Finetune Dataset Builder
Turn raw examples into a training-ready fine-tuning dataset — normalize to the trainer's chat/instruction format, deduplicate (including near-duplicates), strip PII, balance, validate the schema and token lengths, and carve a leak-free eval split. Use when you have raw examples and need a clean, formatted, split dataset before training.
LLM As Judge Scorer
Design a reliable LLM-as-judge metric — a calibrated rubric, a clear scoring scale, and bias controls — and validate it against human labels before trusting it. Use when grading open-ended LLM output (summaries, answers, tone) that exact-match can't score.
LLM Eval Suite Scaffolder
Stand up an evaluation suite for an LLM feature from scratch — a representative dataset, the right metrics, a baseline score, and a CI gate — using DeepEval, promptfoo, or RAGAS. Use when a feature has no evals, before tuning a prompt, or when adding an LLM feature to CI.
Multimodal Document Extractor
Extract structured data from documents and images with a vision-language model — define the target schema, prompt the VLM to fill it from the page (invoices, forms, receipts, statements, IDs), and verify critical fields against the source. Use when you need reliable structured output from messy, varied, or scanned documents that defeat template-based OCR.
Qlora Finetune Runner
Run a QLoRA (4-bit LoRA) fine-tune of an open-weight model from a prepared dataset — set up the config, train memory-efficiently (e.g. with Unsloth/PEFT), watch for overfitting, save the adapter, and run a quick eval against the prepared split. Use when you have a clean dataset and want to execute a parameter-efficient fine-tune on a single GPU.
SQL Optimizer
Diagnose a slow SQL query from its execution plan and propose a verified optimization — finding the real bottleneck (sequential scan, missing or unused index, bad join order, app-side N+1) and measuring the fix before and after. Use when a query is slow and you need a fix backed by EXPLAIN ANALYZE, not a guess.
Embedding Index Tuner
Tune a vector index — HNSW graph parameters and quantization — to hit a recall target at the lowest latency and memory, by sweeping settings against a fixed query set instead of trusting defaults. Use when vector search is slow or memory-hungry, when recall dropped after enabling quantization, or when standing up an index and you need defensible parameters.
Postgres Index Strategist
Recommend the right Postgres index for a query or workload — choosing B-Tree vs. GIN vs. BRIN vs. partial/covering/expression, checking for redundant or unused indexes, and verifying the choice against the query plan. Use when a query needs an index, when deciding an index type for jsonb/array/full-text/time-series data, or when auditing an over-indexed table.
Adr Writer
Write an Architecture Decision Record capturing a decision the user describes, in Michael Nygard ADR format (Status, Context, Decision, Consequences) with an added Considered Alternatives section. Use when recording a significant architectural or technology choice.
OpenAPI Doc Writer
Produce and maintain OpenAPI documentation for an HTTP API. Use when documenting endpoints, request/response schemas, or generating API reference docs.
Readme Generator
Generate or refresh a project README grounded in the actual repository. Use when a project has no README, a stale one, or you want install/usage/scripts/structure sections that match the real code.
Branch Rebaser
Rebase the current branch onto its base and walk every conflict methodically, resolving each by understanding both sides. Use when your feature branch has fallen behind main and you want a clean, linear history without clobbering changes.
Conventional Commits
Generate clear Conventional Commits messages from staged changes. Use when committing code and you want a well-structured, consistent commit message.
PR Description
Draft a clear pull request description from the branch diff against its base. Use when you have a finished branch and want a reviewer-ready PR body before opening the PR.
Bundle Analyzer
Analyze a JS/TS production bundle and surface the biggest size wins — heavy dependencies, duplicate packages, missing code-splitting, oversized polyfills, and dev/server code leaking into the client. Use when a bundle is too large and you need a ranked, actionable reduction plan.
Prompt Cache Optimizer
Restructure an LLM call to maximize prompt-cache hit rate and add response/semantic caching — move the stable prefix (system prompt, instructions, few-shot, context) to the front and variable input to the end, set cache breakpoints, and measure the hit rate and savings. Use when repeated calls share large common context and token cost or latency is too high.
Dead Code Finder
Find genuinely unused code — unreferenced exports, unreachable files, and unused dependencies — and remove it safely with build/test verification. Use when trimming a codebase or untangling years of accreted cruft.
Changelog From PRs
Draft a release changelog by summarizing merged pull requests since the last tag. Use when preparing a release or writing release notes.
Dependency Audit
Audit project dependencies for known vulnerabilities and turn the raw scanner output into a triaged, prioritized upgrade plan. Use when an audit is noisy, a CVE was reported, or you need to know which advisories actually matter.
LLM Guardrails Designer
Design input and output guardrails for an LLM app — decide what to check (injection patterns, PII, secrets, policy, schema, leakage, toxicity), place them as input vs. output rails, implement with a library like NeMo Guardrails or LLM Guard, and fail closed. Use when adding a safety/validation layer around an LLM, not relying on the prompt alone.
Prompt Pii Redactor
Detect and redact PII and secrets from prompts (and logs/traces) before they reach an LLM provider — mask or tokenize emails, phone numbers, names, IDs, and API keys, reversibly where the response needs the real values back. Use when sending user or document data to a third-party model, or when LLM request logs may capture sensitive data.
Secret Scanner
Scan a repo or a diff for committed secrets — API keys, tokens, private keys, .env files, and high-entropy strings — then triage real leaks from fixtures. Use before pushing, in review, or when a credential may have leaked.
Coverage Gap Finder
Run the project's coverage tool and identify the highest-value untested paths — error branches, edge cases, and critical modules — then propose specific test cases for each gap. Use when you have a coverage report but don't know where new tests will pay off most.
Mock Data Factory
Generate a typed mock/fixture factory for a given type, interface, or schema, inferring believable values from field names and types. Use when tests or local dev need realistic, type-safe sample data with per-field overrides.
Test Scaffolder
Scaffold a test file with sensible cases for a given module or function. Use when adding tests to untested code and you want a fast, structured starting point.
Human In The Loop Gate
Add a human approval checkpoint to an agent so it pauses before a risky or irreversible action (spending money, deleting data, sending messages, merging code) and resumes only after a human approves. Use when an agent acts autonomously on consequential operations.
Prompt Optimizer
Diagnose why a prompt underperforms and rewrite it with the technique that fixes it — clearer structure, few-shot examples, an explicit output contract, or reasoning scaffolding — returning an optimized prompt, the rationale for every change, and what to measure to confirm the lift. Use when a prompt is flaky, verbose, drifting in format, or just not good enough.
Frequently asked questions
- What is a Claude Code skill?
- A skill is a reusable capability packaged as a SKILL.md file plus optional supporting files. Claude loads it on demand — only when the task calls for it — so it extends Claude with specialized expertise without bloating every conversation.
- How do I install a skill?
- Save the skill to ~/.claude/skills/<name>/SKILL.md for all your projects, or .claude/skills/<name>/SKILL.md inside a single project. Multi-file skills keep their resources in the same folder. Claude loads it automatically when relevant.
- How are skills different from agents?
- Skills load on demand into your main conversation to add expertise, using progressive disclosure. Agents run as separate subagents with their own isolated context window. Use a skill for know-how, an agent for delegated work.
- What is progressive disclosure?
- Progressive disclosure means Claude only reads a skill's full instructions when the current task matches it. The skill's short description is always visible; its detailed body loads just-in-time, keeping your context lean.
- Are these skills free?
- Yes. Every skill on AgentsCamp is free to copy, download, and install. They are open files with no signup required.