m2ai-agent-ops

Plugin m2ai-agent-ops from marketplace m2ai-skills-pack in m2ai-portfolio/m2ai-skills-pack. Commands read from the repo's manifest — 2 days ago.

Skills (17)

• aar

  Run an After-Action Review on an agent dispatch run, build execution, or multi-step orchestrated operation. Gathers forensics across the orchestrator DB, A2A endpoints, pm2 logs, git history, and queue files; classifies failure modes; captures benchmarks; produces a structured AAR. Use when the user

• action-outcome-postmortem

  Structured post-mortem for the failure mode where an agent executed the correct mechanical action but produced the wrong outcome — the action succeeded, the goal failed. Walks through what semantic context was missing, where to add it, and how to prevent recurrence. Use when an agent did exactly wha

• agent-cold-start-diagnostic

  Evaluate an existing agent setup (CLAUDE.md, SOUL.md, memory files, cron config, agent.yaml) and score it on operational completeness -- flagging missing decision frameworks, vague delegation instructions, absent escalation rules, and gaps in rhythm/schedule coverage. Use when the user says "cold st

• agent-correction-capture

  Document and implement the pattern for capturing user corrections to agent output as structured events (user_correction_submitted). Use when building any agent-facing UI, CLI, or chat interface where you want corrections to flow into an evaluation or feedback pipeline rather than being silently disc

• agent-doctor

  Run a comprehensive health check on all connected services, API credentials, MCP servers, tools, and external dependencies. Validates that everything the agent needs is reachable and authenticated before the user hits a failure. Use as a startup diagnostic or on-demand when things feel broken.

• agent-environment-optimizer

  Audit an agent's execution environment for cold-start patterns, missing warm caches, stale dependencies, and session persistence gaps. Scores against best practices from OpenAI Hosted Shell and METR research showing unoptimized environments negate AI productivity gains. Use when the user says "optim

• agent-run-schema

  Reference skill containing the canonical 10-event agent analytics schema. Defines event shapes (agent_run_started, task_completed, user_correction_submitted, approval_granted, approval_denied, tool_call_failed, memory_miss, run_completed, run_failed, run_aborted) with a shared agent_run_id field tha

• agent-standup

  Run a structured standup across a multi-agent team. Each agent reports status (what completed since last standup), blockers, and next planned action. Produces a shared war-room log with cross-agent dependencies and escalations surfaced. Use when asking for a "standup", "team status check", "/standup

• completion-vs-acceptance

  Analyze the gap between an agent's self-reported completion rate and the actual acceptance rate (tasks the user or downstream validator kept without correction). Produces a 2x2 quadrant — Trusted, Overconfident, Conservative, Failing — for each workflow type. Use when the user says "completion rate"

• diagnose

  Strict 4-gate diagnostic protocol for bugs, failures, and broken pipelines. Forces stating the error, gathering logs/env/recent-changes, listing 3 ranked hypotheses, and getting explicit user approval BEFORE any code edit. Use when the user reports a bug, something is broken, a test is failing, a se

• failure-asymmetry

  Compare a skill's behavior under human invocation vs simulated agent invocation, highlighting divergences in output format, context assumptions, and error paths that only surface without human oversight.

• failure-postmortem

  Guide a structured AI system failure post-mortem using 6 named failure patterns, producing a publishable incident report.

• hallucination-audit-trail

  Cross-checks an agent's self-reported processing log against filesystem evidence (file modification timestamps, existence, size) to detect hallucinated audit trails before they propagate downstream.

• open-loop-audit

  Audit open loops and classify each as real delegation candidate vs simulated work using Nate's "land or leave" framework

• session-work-log

  Produces a structured session-end artifact capturing what was attempted, what changed, what blocked progress, and what the next agent or session needs to know. Machine-readable by design -- survives model swaps and cross-agent handoffs. Trigger phrases: \"write a work log\", \"session work log\", \"

• simulated-work-detector

  Recurring audit that reviews agent fleet output and flags simulated work that generated artifacts but didn't close any loops or remove work from your plate

• trace-prompt

  Reconstruct a sanitized diagnostic trace of the CURRENT prompt exchange only, not the full session, and write it to a markdown file the user can share for support or bug reports. Captures the exact prompt, which model/brain was active (Claude, Codex, Gemini, etc), what tools ran, what happened versu

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