Total 50,552 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
Honestly evaluate AI work quality using a two-axis scoring system. Use after completing a task, code review, or work session to get an unbiased assessment. Detects score inflation, forces devil's advocate reasoning, and persists scores across sessions.
C-suite orchestration layer. Routes founder questions to the right advisor role(s), triggers multi-role board meetings for complex decisions, synthesizes outputs, and tracks decisions. Every C-suite interaction starts here. Loads company context automatically.
Use this skill ANY TIME the user asks about a specific company. Triggers: "tell me about [company]", "research [company]", "what does [company] do", "who is [company]", "look up [company]", "company deep dive", "due diligence on [company]", "background on [company]", "dig into [company]", "analyze [company]", or evaluating a company for investment, partnership, or sales. MUST be used instead of answering from memory — fetches real-time web data (funding, leadership changes, product launches, news) your training data lacks. Use even for well-known companies. Produces a sourced 360° report covering funding, leadership, product/tech, market position, news, and strategic outlook with dates and URLs. Do NOT use for multi-company competitor monitoring (use competitor-intel) or meeting prep with attendees (use meeting-prep).
Initialize a multi-agent swarm with anti-drift configuration
Detect and classify telemetry anomalies on Cognitum Seed devices
Create and adapt Dynamic Agentic Architecture agents that learn and evolve
Persist and restore agent sessions across conversations with state snapshots
Choose the right fal.ai endpoint for a given task. Modality-organized catalog of production endpoint defaults, text-to-image, image-to-image, text-to-video, image-to-video, and more. Use when the user has not named a specific model, or asks "which model for X", "best endpoint for Y", "what should I use for Z".
Use when fact-checking a single wiki page against its cited sources — verifies that every footnote actually supports its claim and surfaces uncited factual claims. Run after ingesting a high-stakes page or any time you want confidence in one page's accuracy.
Browse and compare wiki knowledge by which AI tool originally produced it. Use this skill when the user says "/memory-bridge", "browse codex memory", "what did codex know about X", "show me claude knowledge", "cross-tool memory", "what does hermes know that claude doesn't", "show me knowledge from <tool>", "compare my AI tool memories", or wants to explore knowledge gaps between tools. Works from any project. Diff mode ("what's different", "unique to codex", "gaps between tools") is the killer feature — it surfaces blind spots between tools that the user may not know exist.
Evaluate Omni AI query generation accuracy by running test prompts through the Omni CLI, comparing generated query JSON against expected results, and scoring accuracy. Use this skill whenever someone wants to evaluate Omni AI, benchmark Blobby, run regression tests, compare AI output across branches or configurations, test prompt variations, measure AI quality, run A/B tests on model changes, assess impact of context changes, or any variant of "run evals", "test Blobby", "benchmark query generation", "compare AI results", "regression test", "how accurate is the AI", or "measure the impact of my changes".
Runs an autonomous delivery loop from an existing PRD to implementation, issue triage, per-slice verification, and final repo validation. Use when the user has already created or approved a PRD and asks to automate to-issues, tickets, triage, ready-for-agent implementation, validation, or production-ready completion.