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Found 12,031 Skills
Create/refresh lean repo memory docs and root AGENTS.md guidance for handoffs, stale status, next steps, or post-work capture.
Implement Cisco's Foundry specification for agentic AI security evaluation systems with multi-agent architecture
Web-based chat interface for Hermes Agent with multi-profile management, streaming chat, and interactive terminal integration
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-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.
Autonomous research agent that reads RESEARCH.md, infers what's needed, dynamically adjusts TODOs, and delegates to the right skill. Supports opt-in BFS mode for autonomous design space search. Respects a configurable supervision policy (presets: manual / checkpointed / autonomous / wild) governing notifications, approval gates, resource limits, and idea-change handling. Proactively surfaces gaps and asks before acting. Trigger phrases: "start research", "continue project", "what's next?", "explore design space", "autoresearch".
For use when students **have completed WG-12 to WG-21** (single-file consolidation blueprint) and are working on **WG-22 Code Splitting** (`agent_core.py` + `main.py`). **First message in a new session**: Display PEAS brand screen and confirm readiness first; after confirmation, **lay out the context** before proceeding to requirement clarification. If **`prompts/` or `templates/`** are missing, copy them from `references/project_assets/` to the project root. Process: Spec Alignment (2d′) → Six-column Contract → **In-session Handoff Implementation** → Acceptance. Starting point: starter_main_wg21.py; Standard reference: reference_agent_core.py + reference_main.py. Triggers: peas-workshop-advanced-coach, PEAS workshop advanced coach, WG-22, code splitting coach, Agent.chat.
使用 parallel sub-agents 为 module 生成多个 radically different interface designs。Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
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.