Total 50,553 skills, AI & Machine Learning has 8484 skills
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Process unstructured external input (meeting transcripts, conversation logs, pasted documents) into structured Basic Memory entities. Extracts entities, searches for existing matches, proposes new entities with approval, creates notes with observations and relations, and captures action items.
This skill should be used for multi-session autonomous agent work requiring progress checkpointing, failure recovery, and task dependency management. Triggers on '/harness' command, or when a task involves many subtasks needing progress persistence, sleep/resume cycles across context windows, recovery from mid-task failures with partial state, or distributed work across multiple agent sessions. Synthesized from Anthropic and OpenAI engineering practices for long-running agents.
Install groove backends, companions, and AGENTS.md bootstrap. Run once per repo.
Orchestration workflow for orchestrator role ONLY. Use when: - Agent's role name (tmux pane title) is "orchestrator"
Bootstrap AGENTS.md as a short table-of-contents plus a structured docs/ directory (architecture, product specs, acceptance tests, ADRs, exec plans, quality grades). Use when AGENTS.md is missing, when asked to "create AGENTS.md", "bootstrap project for agents", or "set up agent context".
Use when working with Anthropic Claude Agent SDK. Provides architecture guidance, implementation patterns, best practices, and common pitfalls.
Integrate PICA into a LangChain/LangGraph Python application via MCP. Use when adding PICA tools to a LangChain agent, setting up PICA MCP with LangChain, or when the user mentions PICA with LangChain or LangGraph.
Validates Stories/Tasks or context via parallel multi-agent review (Codex + Gemini). Merges findings, debates, applies fixes. GO/NO-GO verdict.
ALWAYS invoke this skill at the START of every session before doing any other work. This skill ensures the host project has agent governance rules (skill routing, pre-implementation protocol, issue tracking conventions) installed in its context file. It is idempotent — if rules are already present, it exits silently. Without this skill running first, other swain skills (swain-design, swain-do, swain-release) will not be routable.
Creates, updates, or optimizes an AGENTS.md file for a repository with minimal, high-signal instructions covering non-discoverable coding conventions, tooling quirks, workflow preferences, and project-specific rules that agents cannot infer from reading the codebase. Use when setting up agent instructions or Claude configuration for a new repository, when an existing AGENTS.md is too long, generic, or stale, when agents repeatedly make avoidable mistakes, or when repository workflows have changed and the agent configuration needs pruning. Applies a discoverability filter—omitting anything Claude can learn from README, code, config, or directory structure—and a quality gate to verify each line remains accurate and operationally significant.
Conduct comprehensive research on any topic. Synthesize information from multiple angles, provide structured analysis, and generate detailed research reports.
Use Chanjing TTS API to synthesize speech from text, using user-provided voice