Front-door lead agent for ambiguous goals.

Installs new durable agents into the runtime.

Generates wrapper agents for I/O gaps

Learn RTFS (Reason about The Functional Spec) - the pure functional language for CCOS agents

Reference for all MCP tools exposed by the CCOS server for agent interactions

Guide for creating, registering, and managing CCOS/RTFS capabilities

Common patterns for building agent workflows in CCOS

Expert FinOps guidance covering cloud, AI, and SaaS technology spend. Includes AI cost management, GenAI capacity planning, self-hosted vs managed inference, Anthropic billing, AWS (EC2, Bedrock, SageMaker, GPU rightsizing, Savings Plans, CUR, commitment strategy), Azure (reservations, Savings Plans, AHB, OpenAI PTUs, portfolio liquidity), GCP (Vertex AI, Compute Engine, BigQuery), tagging governance, SaaS management (SAM, licence optimisation, SMPs, shadow IT), AI coding tools (Cursor, Claude Code, Copilot, Windsurf, Codex), ITAM, data platforms (Databricks allocation and governance with DBCU commitments, Microsoft Fabric capacity FinOps with F-SKUs, CU smoothing, reservations, pause/resume, Pro-to-Fabric migration), Snowflake, OCI, and GreenOps (AWS Sustainability Console, CSRD). Use for any query about technology cost, commitment portfolio management, rightsizing, cost allocation, SaaS sprawl, AI dev tool spend, or connecting spend to business value. Built by OptimNow.

Recover accidentally deleted files from the recycle bin.

Semantic documentation architect. Analyzes PROSE CONTENT to organize by concept affinity, eliminate contradictions in explanations, and consolidate scattered ideas.

Bootstrap an implementation plan and coordinate a parallel team of named agents using native Agent Teams.

Use for searching code, finding code patterns, refactoring, and analyzing code structure. NEVER use Grep for Python code.

Orchestrate a fleet of remote PicoClaw workers over SSH for fast, ephemeral one-shot tasks.

Use when creating new skills, editing existing skills, or verifying skills work before deployment

Use when you have a spec or requirements for a multi-step task, before touching code

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification

Use when implementing any feature or bugfix, before writing implementation code

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Use when executing implementation plans with independent tasks in the current session

Use when completing tasks, implementing major features, or before merging to verify work meets requirements

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup