Mission control evals observability
An Open Source Platform For Building Projects With OpenAI's Codex, Claude CLI, And Other Coding LLMs Using Multi-Agent Swarms And Customizable Workflows. Runs On Windows, MacOS, And Linux.
npx -y skills add MN755/Codex-Mission_Control --skill mission-control-evals-observabilityAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Design or run evaluation, tracing, callback, telemetry, and regression-observability workflows for Mission Control agents.
SKILL.md
1.8 KB, as published. Nobody here has run it
Mission Control Evals And Observability
Purpose
Make agent quality measurable with evals, traces, evidence, and regression checks instead of vibes in a trench coat.
The Codex chat agent is not the Mission Control Manager. It is the bridge between the user and the Mission Control Manager.
Use when
- The user wants evals or quality gates.
- Agent behavior needs traceability.
- A workflow needs regression tests or benchmark cases.
Workflow
- Ask Mission Control to identify success criteria and failure modes.
- Define eval cases, expected outputs, evidence checks, and scoring.
- Capture trace points for model calls, tools, approvals, and handoffs.
- Summarize results and recommend gates.
Mission Control calls
Tools:
mission_control_start_taskmission_control_get_event_digest
Resources:
mission-control://projects/{project_id}/validation-summarymission-control://projects/{project_id}/orchestrations/{orchestration_id}/eventsmission-control://projects/{project_id}/handoff
User-facing output
- Include eval cases, pass/fail status, trace coverage, regressions, and evidence gaps.
Approval behavior
Ask before running costly model/API eval suites or uploading traces externally.
Never do
- Do not call an eval meaningful without representative cases.
- Do not log secrets in traces.
- Do not reduce quality to a single opaque score.
Failure and fallback
If automated evals are unavailable, produce a manual eval rubric and seed cases.
Example invocation
Use Mission Control to design evals for the Ollama worker edit path.