Agent skill

Retro

by Necmttn in Necmttn/ax

Guided experiment-loop retrospective over the ax agent-experience graph.

AGPL-3.0Auto-check passedProduct & Project Management

Install Retro

skills CLI
$ npx skills add Necmttn/ax --skill retro -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Necmttn/ax retro --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Necmttn/ax.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/retro .claude/skills/retro && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
retro
GitHub stars
116
Token cost
~3.5k tokens
SKILL.md length
1,701 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Guided experiment-loop retrospective over the ax agent-experience graph.

  • Works in 6 steps: Drain pending session retros → Snapshot → Triage open proposals → …
  • The user says lets do an ax retro
  • SKILL.md covers When to fire, Defaults, Workflow and How to track feedback, plus 3 more sections
  • Calls jq

What it does

Retro is an agent skill from Necmttn/ax. Guided experiment-loop retrospective over the ax agent-experience graph. Walks the user through their open proposals (accept-with-scaffold or reject), pending verdicts (confirm the suggested verdict or override), and recent harness-hook effectiveness signal. Triggers when the user says "let's do an ax retro", "ax retrospective", "review my ax proposals", "triage proposals", "experiment loop status", "lock pending verdicts", "hook effectiveness review", "intervention review", "self-improvement session", or invokes…

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Product & Project Management, covering Retrospectives and Proposals and quotes. The repository describes itself as: the agent experience layer · observability + memory for AI coding agents (Claude Code + Codex) · local-first, typed, yours. The licence is AGPL-3.0.

When your agent uses it

  • The user says lets do an ax retro
  • Ax retrospective
  • Review my ax proposals
  • Triage proposals

Example prompts

  • “s do an ax retro”
  • “ax retrospective”
  • “review my ax proposals”
  • “/retro”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Drain pending session retros
  2. Snapshot
  3. Triage open proposals
  4. Verdict review
  5. Hook effectiveness pass (optional)
  6. Close out

What it can do on your machine

Read from SKILL.md and the folder at commit fca259c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Retro loads about 3.5k tokens when it runs. Until then it costs about 159 tokens; SKILL.md has 1,701 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~159
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Necmttn/ax at commit fca259c, republished under its AGPL-3.0 licence (© Necmttn). 1,701 words, ~3,541 tokens.

Download SKILL.mdSave it as .claude/skills/retro/SKILL.md (or your agent's skills folder).
name
retro
description
Guided experiment-loop retrospective over the ax agent-experience graph. Walks the user through their open proposals (accept-with-scaffold or reject), pending verdicts (confirm the suggested verdict or override), and recent harness-hook effectiveness signal. Triggers when the user says "let's do an ax retro", "ax retrospective", "review my ax proposals", "triage proposals", "experiment loop status", "lock pending verdicts", "hook effectiveness review", "intervention review", "self-improvement session", or invokes /ax:retro. Reads/writes via the local `ax improve` and `ax hooks` CLIs. Do NOT auto-trigger on unrelated work.

ax:retro - guided experiment-loop session

Closes the self-improvement loop. Claude orchestrates ax improve … commands; the user decides each row.

Assumes ax (axctl) is on PATH. If ax improve list fails, tell the user to check docs/development.md#setup (DuckDB dylib setup - no daemon required) and stop.

When to fire

ONLY fire on explicit triggers:

  • "let's do an ax retro" / "ax retrospective" / "retro time"
  • "review my ax proposals" / "triage proposals"
  • "what's my experiment loop status" / "lock pending verdicts"
  • "hook effectiveness review" / "intervention review"
  • "self-improvement session"
  • /ax:retro slash command (if the plugin marketplace publishes one)

Do NOT fire on a generic "look at my recent work" - that risks dragging unrelated context into the loop.

Defaults

  • Window for hook signals: last 7 days. Widen to 30 if evidence is sparse.
  • Don't apply changes silently. Every accept/reject/verdict gets the user's explicit yes per row.
  • The retro is read-mostly. Its side-effects are the Step 1 checkpoint measurements, the task briefs accept emits, and verdict locks.

Workflow

Step 0 - Drain pending session retros

Before the proposal queue, check whether prior sessions still owe a retro. This is the "quota arbitrage" path - idle Opus budget chews through the backlog so the experiment loop has signal next time.

  1. Run:

    bash
    ax retro pending --since=7 --idle-min=30 --json

    Returns sessions in the last 7 days that have no reviewed graph edge yet AND look finished (explicit ended_at, or last turn is

    30min idle). If the list is empty, skip to Step 1.

  2. Show the list to the user as 1 line per session (project · turns · model · reason). Ask:

    N session(s) pending retro. Want me to dispatch the retro-reviewer subagent for all of them in parallel, or pick a subset?

  3. On all or <subset>: for each chosen session, write a brief:

    bash
    ax retro brief --session=<session_id>

    This writes .ax/tasks/retro/<key>.md with frontmatter (transcript path, suggested model, turn count, etc.) and a body that tells the reviewer what to do.

  4. Dispatch one retro-reviewer subagent per brief, in parallel. Pass each brief path in the prompt; let the subagent's frontmatter pin model: opus (override per session if suggested_model differs and the user asked you to economize).

    If the retro-reviewer subagent type doesn't resolve (not installed, or the active harness is not Claude Code), read and review the brief INLINE using its required-output instructions instead of abandoning the backlog.

  5. Wait for all subagents. Aggregate results: counts of retros emitted, proposals recommended, model-fit suggestions. Render as a short summary. The user does not approve retro emissions per row - the subagent already wrote them. The user DOES decide on resulting proposals in Step 2.

  6. The reviewed edge now exists for each drained session, so a re-run of ax retro pending should show fewer rows.

If the user declines Step 0, move on. The backlog stays - next retro picks it up.

Step 1 - Snapshot

Measure first, then read. The checkpoint pass is what turns due windows into current ones; a verdict read taken before it reports whatever the last run happened to leave behind.

  1. Run the prerequisite ALONE and wait for it:

    bash
    AX_NO_AUTO_INGEST=1 ax improve checkpoint --json

    It reads the published snapshot and writes checkpoint judgments only - no transcript parsing, no guidance edits, no verdict locks. Leave --force out of an ordinary retro; it rewrites unreviewed windows that are already current.

  2. On success, run the reads (parallel is fine). Prefix EVERY command - a prefix on the first one leaves the freshness drive on for the rest:

    bash
    AX_NO_AUTO_INGEST=1 ax improve list --status=open --json
    AX_NO_AUTO_INGEST=1 ax improve list --status=accepted --json
    AX_NO_AUTO_INGEST=1 ax improve verdict --json
    AX_NO_AUTO_INGEST=1 ax retro list --since=7 --json        # cluster-derived friction summary
    AX_NO_AUTO_INGEST=1 ax hooks summary --since=7 --tail=20  # optional; tolerate failure
  3. If the checkpoint run fails, tell the user measurement is unavailable and continue with proposal review only. Any suggestion already stored belongs to an earlier run - report it as that, and skip the verdict step.

  4. If the checkpoint result reports cacheRefreshRequired above zero, the opportunity evidence needs deriving; say so, and treat those experiments as unmeasured. When the user asks for current evidence, run three operations in order, each awaited on its own: ax ingest (wait for successful publication), the checkpoint prerequisite, then the reads.

ax retro list reflects three pattern types now:

  • tool failures (skill form) -> Pre-<Tool> guard proposals
  • correction pressure (guidance form) -> "Reduce recurring user corrections" proposals targeting CLAUDE.md
  • friction kinds (skill form, one per kind) -> Address recurring <kind> friction proposals

If any of those surfaced, mention them so the user knows to triage in Step 2.

Compute counts: open proposals (by form), accepted experiments with locked_verdict IS NONE, and - separately - experiments whose current view carries a current_reason (insufficient data or a lifecycle state). Then render to the user as 2-4 lines, e.g.:

7 open proposals (3 skill, 4 guidance). 2 accepted experiments are waiting on a verdict. Hook activity last 7d: 142 invocations, 3 blocking errors. Want to triage proposals first, lock the pending verdicts, or skim hook signals?

If both proposal/verdict queues are empty: tell the user nothing's due and offer ax ingest --derive-only to refresh evidence.

Step 2 - Triage open proposals

Order open proposals by frequency desc. For each, in turn:

  1. Run ax improve show <dedupe_sig> --json (or reuse the row from step 1).

  2. Render as 3-5 lines. Example for a skill proposal:

    Schema change guardrail (skill · freq=9 · confidence=high) Hypothesis: schema edits often surface in fix-chains within ~14d. Trigger: fix commits overlap schema files. Behavior: run schema lint + one read/write smoke before edit.

  3. Ask the user: accept, reject, or skip.

  4. Branch:

    • accept → run ax improve accept <dedupe_sig>. By default this emits a TASK BRIEF and returns its task_path; it does not install the artifact. Report that path. Offer: "Want me to implement the brief now?" If yes: implement it, then run ax improve lint so ax reconciles the marker it finds on disk and records the installed artifact. Until lint records one, the experiment has no measurable installation.
    • reject → ask for a short reason (≤80 chars). Run ax improve reject <dedupe_sig> --reason "<reason>".
    • skip → no command. Move on; the proposal stays open for the next retro.

After the loop, summarize: "Accepted 3, rejected 1, skipped 2."

Show full SKILL.md (743 more words)Show less
Step 3 - Verdict review

For each experiment whose latest checkpoint is unlocked (locked_verdict IS NONE), in age order:

  1. Run AX_NO_AUTO_INGEST=1 ax improve verdict <dedupe_sig> to fetch the experiment + checkpoint history.

  2. When the current view carries a current_reason, there is no suggestion to confirm. Report the reason as it is - no opportunities in the window, no detector for this form, retired - and move to the next experiment. A suggestion in the checkpoints history is history, not a recommendation.

  3. Otherwise render the current checkpoint as 2-3 lines:

    Schema change guardrail - +30s checkpoint 12 opportunities in window, 8 addressed (66%) - observed use. Suggested: adopted.

  4. Ask the user to confirm the suggested verdict OR override:

    • adopted (artifact is doing real work)
    • ignored (user wrote it but never invoked it)
    • regressed (it made things worse)
    • partial (mixed signal)
    • no_longer_needed (pattern self-resolved; trigger stopped firing)
  5. Run ax improve verdict <dedupe_sig> --set <verdict> to lock it. All five values stay available to the user by hand, including no_longer_needed, which the algorithm never suggests on its own.

Step 4 - Hook effectiveness pass (optional)

Only run if the user asked for hook review OR if step-1 found ≥3 blocking errors. Light touch - this section is read-only.

  1. Show top hooks from ax hooks summary --since=7 --tail=20 if not already shown.

  2. If a hook keeps blocking, ask: "Want to inspect a recent invocation?" Then run ax hooks invocations --command="<hook>" --tail=5 and render.

  3. Backtest known feedback cases:

    bash
    ax hooks cases enforce-worktree --tail=50 --window=3

    Treat each backtest result as one case type. Report pass/fail/ inconclusive counts.

  4. Interpretation:

    • A blocking hook error is not automatically bad. If the next few agent actions show corrected behavior, it's a useful corrective signal.
    • A successful hook is not automatically useful. Look for downstream behavior change.
    • hook_progress without a terminal success/blocking event is a telemetry gap unless correlated with visible behavior.
    • Prefer deterministic backtests over model judgment.
    • To author a NEW guard from a recurring failure: ax hooks init, write a defineHook hook in ~/.ax/hooks/, ax hooks backtest it against history, then ax hooks install --providers=claude,codex.
Step 5 - Close out

Output a one-paragraph summary:

  • Counts: accepted / rejected / skipped / verdicts locked.
  • Any scaffolded SKILL.md files that still need refinement.
  • When the next retro is recommended. Compute: earliest experiment.created_at + 7d among accepted-but-unlocked experiments, formatted as "next retro suggested around YYYY-MM-DD".

Then ask whether the user wants to commit the scaffolded skill files + proposal-status changes (DB is local, but SKILL.md files are on disk and may belong in version control).

How to track feedback

The retro itself produces durable signal that the experiment loop already captures:

  • Acceptance rate by form - after the session, derive from proposal.status. If skill-form gets accepted 80% but guidance gets rejected 80%, the derive-proposals stage is over-eager on the wrong form. Surface as an observation.

  • Reject reasons - proposal.reject_reason is a free-text corpus. After the session run:

    bash
    ax improve list --status=rejected --json | jq '.[].reject_reason'

    Look for repeated phrases ("duplicate of existing hook"). When a pattern emerges, the derive-proposals stage should dedupe against it

    • tell the user.
  • Verdict surprises - when the user overrides a suggested verdict, note it. Repeated overrides mean the verdict math is biased.

These are observations, not actions. Report in the close-out; don't write to insight tables.

CLI reference Claude calls

bash
ax improve list [--form=skill|subagent|hook|guidance|automation] \
                [--status=open|accepted|rejected|superseded|all] [--json]
ax improve show <dedupe_sig> [--json]
ax improve accept <dedupe_sig> [--force]
ax improve reject <dedupe_sig> --reason "<text>"
ax improve verdict [<dedupe_sig>] [--set <verdict>] [--json]
ax improve checkpoint [--force]            # Step 1 prerequisite; --force only on request
ax improve reset --yes                     # destructive; only when user requests

ax retro pending [--since=N] [--idle-min=N] [--json]   # Step 0 backlog
ax retro brief --session=<id> [--out-dir=<path>] [--json]
ax retro emit --session=<id> [--source=<src>] [--from-file=<json>]
ax retro list [--since=N] [--limit=N] [--json]

ax hooks summary [--since=N] [--tail=N]
ax hooks invocations [--command="<name>"] [--tail=N]
ax hooks cases <case-name> [--tail=N] [--window=N]

--force on accept overwrites an existing SKILL.md scaffold. Only use when the user explicitly says so.

reset --yes wipes ALL proposal/experiment/checkpoint state. NEVER run without explicit user confirmation in this session.

Failure modes

  • ax improve list returns empty → run ax ingest --derive-only once, retry. If still empty, evidence is genuinely thin; tell the user.
  • ax improve accept reports scaffold_exists → ask the user if they want --force or to abandon.
  • ax improve verdict --set reports verdict_locked → that experiment is already finalized; show the locked value and move on.
  • ax improve checkpoint fails → measurement is unavailable for this retro. Say so, skip Step 3, and keep Step 2 going.
  • ax hooks summary returns nothing → retry with --since=30; if still empty, the hook telemetry pipeline is idle, surface as a TODO.
  • Read/query error → tell the user to check docs/development.md#setup (AX_DUCKDB_DYLIB).

Anti-patterns

  • Don't dump raw JSON. Render summaries.
  • Don't run ax improve accept for every open proposal in a batch; the user must say yes per row.
  • Don't write to ~/.claude/skills/ directly. The CLI handles that.
  • Don't propose deleting a scaffolded SKILL.md mid-retro; that's a separate cleanup task.
  • Don't auto-implement experiments from the hook pass. Recommendations only; the user decides + commits.

© Necmttn, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/retro of Necmttn/ax.

Open the folder on GitHubat commit fca259c

Compare with similar skills

Retro next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Retro compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Retro this skillNecmttn/ax116—~3.5kAutomated safety check: PassAGPL-3.0
Self Retrospectivekid0317/crewai_mas_demo164—~505Automated safety check: PassNone
Harness ReckoningFairladyZ625/harness-anything225—~768Automated safety check: PassAGPL-3.0
Weekly Engineering Retrogarrytan/gstack136k—~2.4kAutomated safety check: PassMIT
Dough Execute Planterryyin/lizard2.6k—~4.3kAutomated safety check: PassCustom licence
Oral Paper SkillAdkid-Zephyr/oral-paper-skill350—~1.9kAutomated safety check: PassNone

Similar skills

  • Self Retrospective

    kid0317/crewai_mas_demo

    Agent 自我复盘:读取 L2/L3/L1 日志,调用 LLM 生成结构化改进提案, 写入 proposals.json 并发通知至 human.json 等待审批。

    164 GitHub stars~505 tokensUpdated 4 mo ago
    Product & Project ManagementAuto-check passed
  • Harness Reckoning

    FairladyZ625/harness-anything

    Run and interpret a read-only retrospective over Harness ledger projections, then prepare evidence-backed mechanism fixes, deletion candidates, or time-bounded rule proposals for human adjudication.

    225 GitHub stars~768 tokensUpdated today
    Product & Project ManagementAuto-check passed
  • Builds a weekly engineering retrospective from git history: commit counts, per-person contributions, work patterns and code quality numbers over a chosen window.

    136k GitHub stars~2.4k tokensUpdated today
    Product & Project ManagementAuto-check passed
  • Dough Execute Plan

    terryyin/lizard

    Executes one selected story or bounded retrospective correction through an executable plan, or one authorized planless slice from a selected simple story or a contextual instruction, with…

    2.6k GitHub stars~4.3k tokensUpdated 3 days ago
    Product & Project ManagementAuto-check passed
  • Oral Paper Skill

    Adkid-Zephyr/oral-paper-skill

    Help authors learn from exemplary ICLR, ICML, and NeurIPS papers through source-linked manuscript comparisons, concrete writing and experiment suggestions, and guided reflection.

    350 GitHub stars~1.9k tokensUpdated 22 days ago
    Product & Project ManagementAuto-check passed
  • Deck Retro

    asheshgoplani/agent-deck

    Run a fully local agent-deck retrospective over the user's own transcripts, Recall index and logs.

    1k GitHub stars~1.8k tokensUpdated 4 days ago
    Product & Project ManagementAuto-check passed

More from Necmttn/ax

All 12 skills in this repo
  • Tune

    Necmttn/ax

    Retrospective on one coding session that proposes changes to the agent's environment (hooks, checks, steering files, tool access) and files each as an ax proposal.

    116 GitHub stars~1.3k tokensUpdated 2 days ago
    Auto-check passed
  • Ax Narrate

    Necmttn/ax

    Write the agent-generated narration of the current session - the reviewable story of what changed, including what never reaches a PR (user corrections, abandoned attempts, tool failures).

    116 GitHub stars~1.7k tokensUpdated 2 days ago
    Auto-check passed
  • Ax Repo

    Necmttn/ax

    Star the ax repo, file an issue / bug report, or fork-and-open-a-PR against github.com/Necmttn/ax on the user's behalf, by shelling out to the gh CLI.

    116 GitHub stars~1.8k tokensUpdated 2 days ago
    Auto-check passed
  • Draft or revise ax release announcements and website changelog pages.

    116 GitHub stars~1k tokensUpdated 2 days ago
    Auto-check passed
  • Retro Meta

    Necmttn/ax

    Deep retro of retros - investigation pass that surfaces improvements across older retros and the current ax setup.

    116 GitHub stars~1.8k tokensUpdated 2 days ago
    Auto-check passed
  • Setup

    Necmttn/ax

    Install + verify ax (the agent experience layer). An agent skill from Necmttn/ax.

    116 GitHub stars~2k tokensUpdated 2 days ago
    Auto-check passed

Questions about Retro

What does Retro do?

Guided experiment-loop retrospective over the ax agent-experience graph. Retro is an agent skill from Necmttn/ax. Guided experiment-loop retrospective over the ax agent-experience graph.

When should I use Retro?

Retro fits situations like: the user says lets do an ax retro; ax retrospective; review my ax proposals; triage proposals.

How do I install Retro in Claude Code?

Run `npx skills add Necmttn/ax --skill retro -a claude-code`. Or copy the skill folder (skills/retro in Necmttn/ax) into .claude/skills/retro in your project. Claude Code loads it when a task matches its description.

How do I install Retro in Codex?

Run `npx skills add Necmttn/ax --skill retro -a codex`. Or copy the skill folder (skills/retro in Necmttn/ax) into .agents/skills/retro in your project. Codex loads it when a task matches its description.

Can I use Retro in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Necmttn/ax --skill retro -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/retro, .gemini/skills/retro, .github/skills/retro and .opencode/skills/retro in your project.

What does Retro need to run?

Going by SKILL.md and its folder, Retro needs the command-line tools its instructions call (jq).

Does Retro access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Retro safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Retro use?

Retro is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Retro use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Retro?

Skills that share tags, products or a category with Retro: Self Retrospective (kid0317/crewai_mas_demo, 164 stars), Harness Reckoning (FairladyZ625/harness-anything, 225 stars), Weekly Engineering Retro (garrytan/gstack, 136k stars) and Dough Execute Plan (terryyin/lizard, 2.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Retro?

Necmttn (a GitHub user) maintains it in Necmttn/ax, which has 116 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 7, 2026.

Source: Necmttn/ax on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.