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Found 11,928 Skills
This skill should be used when running CI checks iteratively and fixing failures. Use when executing make targets (fast-ci, all-ci, ci), iterating on lint/format/type/test errors, or needing the devrun agent pattern for pytest/ty/ruff/prettier/make/gt commands.
Browse and search the Hence gallery (hence.sh) to discover projects built with AI coding agents. Use when the user wants inspiration, wants to see what others have built, asks about projects on Hence, or mentions searching for AI-built projects. Triggers on queries like "show me cool projects", "search Hence", "find CLI tools on Hence", or "what are people building with Claude Code".
Verify that claims and direct quotes in research manuscripts are present in source materials. Systematically checks interview transcripts, datasets, or cited literature using fast search with haiku agent fallback for intensive reading.
Inline risk classification for agent tasks using a 4-tier model. Hybrid routing: GREEN/YELLOW use heuristic file-pattern matching, RED/CRITICAL escalate to war-room-checkpoint for full reversibility scoring.
Terminal-Bench integration for Mux agent benchmarking and failure analysis
Review applications and verify task submissions on OpenAnt. Use when the agent (as task creator) needs to review applicants, accept or reject applications, approve or reject submitted work, or give feedback on deliverables. Covers "review applications", "approve submission", "reject work", "check applicants", "verify task".
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. This skill covers the Interactions API, the recommended way to use Gemini models and agents in Python and TypeScript.
Create, synthesize, and iteratively improve agent skills following the Agent Skills specification. Use when asked to "create a skill", "write a skill", "synthesize sources into a skill", "improve a skill from positive/negative examples", "update a skill", or "maintain skill docs and registration". Handles source capture, depth gates, authoring, registration, and validation.
Bootstrap, install, and operate an external task-management CLI as the source of truth for agent execution tracking (instead of built-in todos). Provides the abstraction layer between spec-management intent (implementation plans and tasks) and concrete CLI commands. MUST be invoked when any implementation-tier artifact (SPEC, STORY, BUG) comes up for implementation — create a tracked plan before writing code. Optional but recommended for complex SPIKEs. For coordination-tier artifacts (EPIC, VISION, JOURNEY), spec-management must decompose into implementable children first — this skill tracks the children, not the container. Also use for standalone tasks that require backend portability, persistent progress across agent runtimes, or external supervision. Use this skill whenever the user asks to track tasks, create an implementation plan, check what to work on next, see task status, manage dependencies between work items, or close/abandon tasks — even if they don't mention "execution tracking" explicitly.
Interact with DeerFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents in DeerFlow, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks to DeerFlow. Also use when the user mentions deerflow, deer flow, or wants to run a deep research task that DeerFlow can handle.
Use the skill-hub CLI to search, install, update, and publish agent skills from skill-hub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed skill-hub CLI.
Probes CLI agents (Codex, Gemini) and writes docs/environment_state.json — agent availability config for Phase 0