Agent skill

Tune

by Necmttn in 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.

AGPL-3.0Auto-check passedProduct & Project Management

Install Tune

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

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

GitHub CLI
$ gh skill install Necmttn/ax tune --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/tune .claude/skills/tune && 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
tune
GitHub stars
116
Token cost
~1.3k tokens
SKILL.md length
713 words
Files
3 (incl. scripts)
Skills in repo
12
Repo updated
First seen
Licence
AGPL-3.0

At a glance

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.

  • Works in 8 steps: Call the Skill tool with… → Locate the session. Default is the… → Make it reviewable in ax, scoped. Run ax… → …
  • The user says environment retro
  • SKILL.md covers Steps and Reference
  • Runs Python scripts from its folder; calls python3

What it does

Tune is an agent skill from 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. Reads the raw session log through a bundled ledger script, with ax as the second source and the ledger. Triggers when the user says "environment retro", "env retro", "what should I change in my setup after this session", "retro this session's tooling", or invokes /ax:tune. Use /ax:retro to triage the proposals it files.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `PROPOSALS.md` and `scripts/turns.py`).

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 environment retro
  • What should I change in my setup after this session
  • Retro this sessions tooling
  • Invokes /ax:tune

Example prompts

  • “environment retro”
  • “env retro”
  • “what should I change in my setup after this session”
  • “/tune”

Requirements

  • Python 3

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Call the Skill tool with writing-for-agents for the writing style.
  2. Locate the session. Default is the current one: the id is $CLAUDE_CODE_SESSION_ID and the log is ~/.claude/projects//.jsonl. If the user…
  3. Make it reviewable in ax, scoped. Run ax ingest here in the background (the bare ax ingest walks every transcript on the machine). Watch…
  4. Build the ledger. Run python3 -I scripts/turns.py (add --full to see each command). It prints one line per tool call with ERR, DENY…
  5. Hunt candidates in these categories, each with evidence from the ledger (turn, tool calls spent, bytes or tokens wasted) and a fix that…
  6. Present the candidates to the user in order of severity: cost in this session first, then likelihood of recurrence. One paragraph each…
  7. File in ax. Read PROPOSALS.md for the payload shapes. Then
  8. Apply only when asked. If the user says fix them, apply in severity order, one commit per repo, and re-run the ledger on the next session…

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

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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

Tune loads about 1.3k tokens when it runs. Until then it costs about 123 tokens; SKILL.md has 713 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~123
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from Necmttn/ax at commit fca259c, republished under its AGPL-3.0 licence (© Necmttn). 713 words, ~1,317 tokens.

Download SKILL.mdSave it as .claude/skills/tune/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
tune
description
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. Reads the raw session log through a bundled ledger script, with ax as the second source and the ledger. Triggers when the user says "environment retro", "env retro", "what should I change in my setup after this session", "retro this session's tooling", or invokes /ax:tune. Use /ax:retro to triage the proposals it files.

ax:tune - what to change in the rig after one session

The user has asked to tune the rig. You read what one session actually did, name the changes to the agent's environment (hooks, checks, steering files, tools, access) that would make the next run cheaper or safer, and file every candidate in ax so it is triageable later. The session log is the primary source; ax is the ledger.

Steps

  1. Call the Skill tool with writing-for-agents for the writing style.

  2. Locate the session. Default is the current one: the id is $CLAUDE_CODE_SESSION_ID and the log is ~/.claude/projects/<cwd-slug>/<id>.jsonl. If the user names another session, take its key. Done when you hold a path that exists.

  3. Make it reviewable in ax, scoped. Run ax ingest here in the background (the bare ax ingest walks every transcript on the machine). Watch its RSS; stop it at 4 GB and record that as a Tool economy finding against ax itself. Continue on the raw log while it runs.

  4. Build the ledger. Run python3 -I scripts/turns.py <log> (add --full to see each command). It prints one line per tool call with ERR, DENY, RETRY, AGENT, BIG flags and a summary of calls, flags and tokens. When ax has the session, add ax sessions show session:<id> --turns --json for timings. Done when every flagged line has a cause you can state.

  5. Hunt candidates in these categories, each with evidence from the ledger (turn, tool calls spent, bytes or tokens wasted) and a fix that names a file.

    • Navigation: the agent took long to find a file or fact. Fix: a pointer in auto-memory or the repo's CLAUDE.md, never a paragraph.
    • Automated checks: a mistake a linter, type check, test or filesystem check would have caught. Read the repo's own check command first (package.json scripts, CI workflow); an existing check that is unwired or broken is the finding. A repo with no pre-commit hook and no CI check is itself a finding.
    • Coding standards: classify the violation first. A mechanical one (banned API, import shape, file-location rule, a command shape) gets a deterministic check: a lint rule, a pre-commit hook, a PreToolUse hook that rewrites and allows rather than denies. Reserve prose rules for judgement calls no check can substitute for, and give them to the reviewer agent, which has the least context pressure.
    • Global AGENTS.md / CLAUDE.md: always-loaded lines that did not bear on this session. Candidates for a pointer and a doc, or deletion.
    • Tool economy: expensive calls. A BIG result, an alias or pager writing ANSI to a pipe, a denial that forced a verbatim resend, a search over the wrong tree. Fix: a rewrite hook, a tty guard, a scoped command.
    • No-ops: steering lines the model already obeys by default. Delete the sentence, not words from it.
    • Information access: a fact the agent needed and could not reach (a session id, a dev-server log, a third-party dashboard). Fix: an env var, a tee, read-only access.

    Done when each candidate has category, evidence, fix, and the file the fix lands in.

  6. Present the candidates to the user in order of severity: cost in this session first, then likelihood of recurrence. One paragraph each. End with which ones are mechanical (a check) and which need judgement (a rule).

  7. File in ax. Read PROPOSALS.md for the payload shapes. Then:

    bash
    ax retro brief --session=session:<id>          # writes .ax/tasks/retro/<id>.md
    ax retro emit --session=session:<id> --source=manual --from-file=<json>

    The JSON holds tried, worked, failed, next, and one proposals[] entry per candidate, shaped by its form. Set the brief's frontmatter status: completed. Done when ax improve list shows the new proposals.

  8. Apply only when asked. If the user says fix them, apply in severity order, one commit per repo, and re-run the ledger on the next session to confirm the flag class is gone.

Show full SKILL.md (88 more words)Show less

Reference

Implementation vs review

Work goes through two stages. The implementation agent explores, writes and debugs under the most context pressure. The review agent receives a diff and has the least. Standards belong to the reviewer; the implementer gets checks and pointers.

Files
  • CLAUDE.md / AGENTS.md: loaded every turn in that repo. Navigation pointers only.
  • CODING_STANDARDS.md: read at review time. Judgement rules.
  • ~/.claude/hooks/*.sh: PreToolUse guards. Prefer permissionDecision: allow with updatedInput over deny.
  • ~/.claude/projects/<slug>/memory/: auto-memory. Pointers and machine-local facts.
  • Skills: docs whose description is a context pointer, or user-invoked commands.

© 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

SKILL.md and 2 other files (scripts) in skills/tune of Necmttn/ax.

  • SKILL.md
  • PROPOSALS.md
  • scripts/turns.py

Open the folder on GitHubat commit fca259c

Compare with similar skills

Tune 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.

Tune compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tune this skillNecmttn/ax116—~1.3kAutomated safety check: PassAGPL-3.0
Self Retrospectivekid0317/crewai_mas_demo164—~505Automated safety check: PassNone
Harness ReckoningFairladyZ625/harness-anything225—~768Automated safety check: PassAGPL-3.0
Tdoctornado-doc/tdoc103—~18kAutomated safety check: NotesAGPL-3.0
Proposal Reviewer ChorusChorus-AIDLC/Chorus1.2k—~3.9kAutomated safety check: PassAGPL-3.0
Weekly Engineering Retrogarrytan/gstack136k—~2.4kAutomated safety check: PassMIT

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Questions about Tune

What does Tune do?

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. Tune is an agent skill from 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.

When should I use Tune?

Tune fits situations like: the user says environment retro; what should I change in my setup after this session; retro this sessions tooling; invokes /ax:tune.

How do I install Tune in Claude Code?

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

How do I install Tune in Codex?

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

Can I use Tune 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 tune -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tune, .gemini/skills/tune, .github/skills/tune and .opencode/skills/tune in your project.

What does Tune need to run?

Going by SKILL.md and its folder, Tune needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Tune 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 Tune 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Tune use?

Tune 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 Tune use?

About 1.3k tokens (SKILL.md is roughly 5.3k 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 Tune?

Skills that share tags, products or a category with Tune: Self Retrospective (kid0317/crewai_mas_demo, 164 stars), Harness Reckoning (FairladyZ625/harness-anything, 225 stars), Tdoc (tornado-doc/tdoc, 103 stars) and Proposal Reviewer Chorus (Chorus-AIDLC/Chorus, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tune?

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.