npx skills add ...
npx skills add necmttn/ax --skill retro-meta
Deep retro of retros - investigation pass that surfaces improvements across older retros and the current ax setup. External AI agent drives the reasoning with high thinking enabled. Triggers when user says "deep retro", "investigate ax", "what should I fix in my setup", "retro of retros", or invokes /ax:retro-meta. Use after `ax:retro` if proposals are sparse or you want broader exploration.
npx skills add necmttn/ax --skill retro-meta
The companion to ax:retro. Where ax:retro walks the heuristic-derived
proposals one by one, retro-meta asks: what improvements does the
existing pipeline NOT yet see?
The external agent (this one, Claude Code or Codex with high thinking) drives the reasoning. The CLI just produces structured evidence and takes user-approved plans back.
Explicit triggers only:
/ax:retro-meta slash commandax:retro finishes if the user wants broader explorationDo NOT auto-trigger on generic "look at recent work".
ax (axctl) is on PATH. If ax doctor fails, stop and point the user at
docs/development.md#setup (DuckDB dylib setup - no daemon required).ax:retro first.Read /tmp/ax-meta.json. The keys you care about:
experiment_status[] - read this FIRST (see Step 2). Each entry:
experiment_id, proposal_dedupe_sig, proposal_title,
proposal_form, artifact_path, days_since_accepted,
opportunities_count, addressed_count, address_ratio,
latest_checkpoint{kind,suggested,observed_at}, locked_verdict.
Pending verdicts (locked_verdict=null) come first.retros[] - raw tried/worked/failed/next per session.patterns.tool_failures - sorted by total_count desc.patterns.corrections - total + max-per-session + session_count.patterns.friction_kinds - recurring kinds across sessions.current_state.skills - what's already installed (do NOT propose
duplicates).current_state.open_proposals - existing heuristic proposals.current_state.accepted_experiments - accepted but verdict-pending.current_state.claude_md_user / claude_md_project - guidance file
paths (null if absent).investigation_prompts[] - the prompts you must walk.Walk experiment_status in order. For each entry with
locked_verdict=null:
a. If latest_checkpoint.suggested is ignored or regressed:
investigate why (read the artifact_path, sample the matching
opportunities), then run
ax improve verdict --set=<v> <proposal_dedupe_sig> to lock the
call.
b. If latest_checkpoint.suggested is adopted AND
days_since_accepted > 30: lock it as adopted so it stops
cluttering the open list:
ax improve verdict --set=adopted <proposal_dedupe_sig>.
c. If latest_checkpoint is null OR suggested is partial: leave
open. Note in the final summary that it's still gathering signal.
A rule of thumb mirrored from investigation_prompts: if
address_ratio < 0.1 after t+30, default to locking as ignored
unless the artifact has an obvious "not yet exercised" reason.
For EACH prompt in investigation_prompts:
~/.claude/skills/ and ~/.agents/skills/claude_md_user if non-nullclaude_md_project if non-null~/.claude/plans/<YYYY-MM-DD>-<slug>.md,
30–100 lines. Sections: Problem, Evidence (cite retro ids),
Proposed change, Success signal.
b. Show the user a 4–6 line summary.
c. Ask explicitly: "Register this as an accepted experiment? (y/n)"
d. ONLY on yes:
For each plan you registered, you may run:
This spawns the internal scaffolding agent to draft an artifact (SKILL.md, hook script, etc) from the plan. Skip if the plan is already self-sufficient.
Print one paragraph:
~/.claude/skills/. Use ax retro plan +
ax improve accept --with-agent.Output of ax retro meta defaults to JSON because the reader is you,
not a human.