Agent Operator Utility Pack
by Corey Jacobs
Five compact skills for artifact intake, preflight review, test planning, session handoff, and local tool-candidate inspection.
Free
Works with the AI tools you already use
See it in action
You say
Review this repo structure and summarize where I left off so I can resume work in a new chat thread.
Your agent does
Context Handoff Spine
Current State: Implemented core CRUD for /users; pending JWT auth.
Active Files: routes/user.js, middleware/auth.js (incomplete).
Next Steps:
- Complete
verifyTokenlogic in auth middleware. - Link middleware to user routes. Residual Unknowns: Token expiry duration?
About this skill
Agent Operator Utility Pack is a compact bundle of five workflow skills for AI builders, developers, and operators who need cleaner artifact review, package preflight checks, test planning, session handoff, and local tool-candidate inspection.
It is designed for moments where an AI-assisted project needs more structure before the next build, review, or handoff step.
Included skills:
Intake Guard: Reviews unknown artifacts, pasted specs, folders, or candidate packages before trusting them.
Zip Preflight Guard: Checks ZIPs and release folders for public-upload risks, missing files, local-only assumptions, and packaging issues.
Test Surface Finder: Helps identify practical test targets and validation surfaces for small repos, scripts, or workflow packages.
Context Handoff Spine: Produces compact handoff notes so another model, session, or operator can continue the work.
MCP Candidate Inspector Lite: Reviews whether a workflow, script, or tool idea is shaped enough to become a local tool candidate.
Why use this skill: AI-assisted work often fails at the handoff points: unclear artifacts, upload folders with missing context, weak test surfaces, incomplete session summaries, or tool ideas that are not ready to become tools yet.
This pack gives operators a small set of reusable review workflows for those transition points.
The output: Depending on the selected skill, outputs may include intake notes, preflight findings, focused test plans, session handoff summaries, local tool-candidate notes, must-fix items, should-fix items, and residual unknowns.
Important boundary: This pack provides workflow review aids and operator structure. It does not certify security, compliance, production readiness, marketplace approval, or official MCP compatibility.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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