200 skills matching “agent skills”
development
Discovers and invokes agent skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.
documentation
--- name: harness-engineering description: This skill should be used when designing autonomous agent harnesses: research loops, evaluation scaffolds, locked and editable surfaces, durable logs, novelty gates, pruning, rollback, PR preparation, and human approval boundaries. --- # Harness Engineering Harness engineering designs the control system around an agent: what it may edit, how it receives feedback, where it writes state, how failures recover, and who can approve irreversible actions. Th
tools
--- name: tool-design description: This skill should be used for the tool-interface layer of an agent system specifically: writing tool descriptions agents can route on, designing tool schemas and response formats, naming conventions, actionable error recovery messages, MCP server design, tool-set consolidation, and deciding when to add or remove an individual tool. Use this when the unit of work is a single tool or a set of tools. Route project-shape, pipeline architecture, and task-model-fit d
development
--- name: project-development description: This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand, the shape of a multi-stage batch or agent pipeline, token and cost estimation, choosing between single-agent and multi-agent at the project level, structured output design for downstream parsing, and structuring agent-assisted iteration. Use this when the unit of work is a whole project or a multi-stage pipeline. R
devops
--- name: hosted-agents description: This skill should be used when designing hosted or background agent infrastructure: sandboxed execution, remote coding environments, warm pools, session persistence, multiplayer collaboration, self-spawning agents, or Modal-style sandboxes. --- # Hosted Agent Infrastructure Hosted agents run in remote sandboxed environments rather than on local machines. When designed well, they provide unlimited concurrency, consistent execution environments, and multiplay
tools
--- name: filesystem-context description: This skill should be used when agent work needs file-backed context: durable scratchpads, tool-output offloading, just-in-time discovery, cross-agent handoff files, filesystem memory, or cleanup policies for context stored outside the prompt. --- # Filesystem-Based Context Engineering Use the filesystem as the primary overflow layer for agent context because context windows are limited while tasks often require more information than fits in a single wi
development
--- name: evaluation description: This skill should be used when building agent evaluation systems: deterministic checks, regression suites, multi-dimensional rubrics, quality gates, production monitoring, baseline comparison, and outcome measurement for agent pipelines. --- # Evaluation Methods for Agent Systems Evaluate agent systems differently from traditional software because agents make dynamic decisions, are non-deterministic between runs, and often lack single correct answers. Build ev
data-ai
--- name: context-degradation description: This skill should be used for diagnosing and mitigating context degradation: lost-in-middle failures, context poisoning, context clash, context confusion, attention-pattern issues, and agent performance degradation caused by accumulated or conflicting context. --- # Context Degradation Patterns Diagnose and fix context failures before they cascade. Context degradation is not binary — it is a continuum that manifests through five distinct, predictable
development
--- name: bdi-mental-states description: This skill should be used when modeling agent mental states with BDI concepts: beliefs, desires, intentions, RDF-to-belief transformations, rational agency traces, cognitive agents, BDI ontologies, and neuro-symbolic AI integration. --- # BDI Mental State Modeling Transform external RDF context into agent mental states (beliefs, desires, intentions) using formal BDI ontology patterns. This skill enables agents to reason about context through cognitive a
data-ai
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
data-ai
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
development
Expert guidance for creating, writing, building, and refining Claude Code Skills. Use when working with SKILL.md files, authoring new skills, improving existing skills, or understanding skill structure and best practices.
documentation
--- name: make_readme description: create or update a meaningful readme # What is a README README.md files are for humans: * quick starts, * project descriptions * contribution guidelines. # Structure a README.md must be structured in, at least, the following paragraphs * Getting started * Introduction * Core Features & Benefits * Core Concepts Explained * Project Structure * Installation * A Simple Example * References
tools
Agent skills collection for legal research and automation
development
# Skill: twitter-agent > Build and run one or more Twitter/X agents, each with a distinct personality, storyline, and post-image library. # Twitter Agent Skill This skill provides a framework for creating, managing, and automating Twitter/X agents with persistent personalities and voices. It supports running multiple agents side-by-side, each with its own files and (optionally) its own X account. ## Prerequisites ### X Account Setup (REQUIRED — Do This First, Per Agent) Every agent's X acco
development
Evaluate and improve Claude Code commands, skills, and agents. Use when testing prompt effectiveness, validating context engineering choices, or measuring improvement quality.
tools
Use when creating Agent Skills packages (SKILL.md format) for Codex CLI, GitHub Copilot, or Amp - provides the agentskills.io specification with frontmatter constraints, directory structure, and validation rules
development
# Skill: /replicate-paper **Trigger:** `/replicate-paper [paper.pdf] [data.csv|dta]` or "replicate this paper" **Purpose:** Full 6-phase autonomous replication of a biomedical/epidemiology paper using UK Biobank or similar data. Produces Python and R scripts plus a polished validation report. --- ## Invocation ``` /replicate-paper papers/AuthorYear.pdf data/ukb_extract.csv ``` Or with just: "replicate this paper" (Claude will ask for paths if not provided). --- ## The 6-Phase Pipeline #
testing
Guide for creating DAAF agent definition files. Covers 12-section template, hook registration, skills-in-frontmatter, integration checklist. Use when adding or revising agents. For SKILL.md files, use skill-authoring instead.
testing
# SKILL: TROUBLESHOOTING & ISSUE RESOLUTION ## STEP 1: CHECK KNOWN ISSUES FIRST **Before trying random solutions:** ```powershell # Search known issues database $errorPattern = "duplicate target juce" $knownIssues = Get-Content ...agent\troubleshooting\known-issues.yaml | ConvertFrom-Yaml $matches = $knownIssues.issues | Where-Object { $_.error_patterns -match $errorPattern } if ($matches) { Write-Host "✓ Known issue found: $($matches.title)" Write-Host "Resolution: $($matches.re