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Found 5,796 Skills
Manage durable working-session memory for coding agents. Use when a user asks to preserve or recover agent context across disconnects, VS Code restarts, long-running work, handoffs, or any session where important state should be written periodically under the repo's session directory.
Generates a daily standup post from GitHub activity and agent session history, and posts it to the mitodl/hq Check-ins discussion. Use when asked to write, generate, or post a daily standup — fetches PR, issue, and code-review activity via the gh CLI, queries recent agent sessions, asks clarifying questions about timing and off-GitHub work, renders the standup in the team's standard format, and posts it as a discussion comment with user confirmation.
Create/refresh lean repo memory docs and root AGENTS.md guidance for handoffs, stale status, next steps, or post-work capture.
OpenAI Agents SDK for JavaScript/TypeScript (text + voice agents). Use for multi-agent workflows, tools, guardrails, or encountering Zod errors, MCP failures, infinite loops, tool call issues.
Brainstorm and validate names for plugins, skills, agents, and commands. Use when naming a new plugin, choosing atom names, validating naming conventions, or when user mentions "name plugin", "name skill", "naming convention", "brainstorm names", "what should I call", "plugin name", "good name for".
Agent Design Consultant and Review Tool. Based on 12-Factor AgentOps best practices, it is used for: (1) Discussing Agent architecture design solutions; (2) Reviewing the design of existing Agents/Skills/workflows, identifying issues, and providing improvement suggestions. Trigger phrases: Review my agent, Help me analyze this skill, Agent design, Agent optimization, Help me review this workflow, What's wrong with this agent, How to design an agent, Agent architecture consultation.
Agent-optimized CLI for Bluesky (ATProto) and X (Twitter). YAML in, YAML out, exit codes for automation. Use when the task involves posting, replying, reading feeds, searching, annotating URLs, or running a sync/check/dispatch agent loop across social platforms.
Render A2UI (Agent-to-UI declarative surfaces) in CopilotKit v2. Enable the runtime via CopilotRuntime({ a2ui: {...} }), then enable the provider via <CopilotKitProvider a2ui={{ theme }}>. Auto-activates via /info — do NOT manually pass renderActivityMessages. createA2UIMessageRenderer ships from @copilotkit/react-core/v2; low-level primitives (A2UIProvider, A2UIRenderer, createCatalog) ship from @copilotkit/a2ui-renderer. Covers theme customization, createSurface dedup, action-bridge try/finally cleanup. Load when an agent emits A2UI operations (createSurface / updateComponents / updateDataModel), when wiring a2ui on CopilotRuntime, or when styling A2UI surfaces.
Build a complete agent-readable Obsidian vault for a Tailwind-based web codebase, eight flat top-level domain docs (PRODUCT/RUNTIME/ARCHITECTURE/DATA/AUTH/ENGINEERING/TESTING/DESIGN), folder-level deep specs, bidirectional wikilinks for graph navigation, and a `DESIGN.md` that conforms to the google-labs-code/design.md spec with tokens derived from `tailwind.config.{ts,js}` or the v4 `@theme` block. Use when asked to "set up project docs", "write project documentation", "create an Obsidian vault from this repo", "document this codebase for agents", "add a DESIGN.md", or "make the design system machine-readable".
The first Outlook calendar CLI built for AI agents on personal Microsoft 365 accounts — with offline conflict... Trigger phrases: `what's on my calendar today`, `find me an hour next week`, `do I have any conflicts`, `what meetings haven't I responded to`, `prep me for my next meeting`, `schedule a meeting on my Outlook calendar`, `use outlook-calendar`, `run outlook-calendar`.
Augment a Wren project with business context that DB schema cannot carry — enum value meanings, units (USD vs cents, ms vs sec), NULL semantics, magic sentinels (-1 = unknown), soft-delete default filters, business synonyms, time-grain / TZ conventions, cross-system identifiers, currency rules, canonical-table preferences, AND named aggregation metrics (ARR, churn, DAU, WAU, NRR) proposed as cubes. Runs in one of two modes selected at session start: `grill` (one question at a time, user-driven) or `auto-pilot` (agent infers and applies, escalates only on conflicts and high-blast-radius additions like new cubes / views / relationships). Reads everything under <project>/raw/ (PDFs, glossaries, handbooks, code, data dictionaries) and optionally samples low-cardinality columns from the live DB (grill mode), compares against the current MDL / cubes / instructions.md / queries.yml / memory pairs, then fills gaps via the ten-category gap catalog and the cube proposal flow. Confirmed findings are written back to the right sink. Use when: user says 'enrich context', 'augment my project', 'grill me on this project', 'auto-fill my context', 'agent doesn't understand our docs / enum values / units / null meanings', 'business context is missing', 'what does status=A mean', 'is this amount in USD or cents', 'we keep getting wrong aggregations', 'add cubes for ARR / DAU / churn', 'we have a handbook / glossary / data dictionary the agent should know'; or after generating an MDL and noticing the agent lacks business semantics.
Day-one data bootstrapping for a new brain. Sequences the highest-leverage data sources to go from empty brain to useful brain in one session. Uses ClawVisor for safe credential handling — the agent never holds raw API keys. Covers Gmail import, calendar sync, contacts seeding, X/Twitter archive, conversation imports, and file archives. Use when a user has just finished gbrain setup and asks "now what?"