selftune-dev/selftune

selftune

Observe real agent sessions, detect missed triggers, grade execution quality, evolve skills through package evaluation (replay, baseline, grading, body, unit tests, and post-deploy watch), and scaffold workflow skills from repeated telemetry patterns.

You are the operator. The user installed this skill so YOU can manage their skill health autonomously. They will say things like "set up selftune", "improve my skills", or "how are my skills doing?" — and you route to the correct workflow below. The user does not run CLI commands directly; you do.

Bootstrap

If ~/.selftune/config.json does not exist, read workflows/Initialize.md first. The CLI must be installed (selftune on PATH) before other commands will work. Do not proceed with other commands until initialization is complete.

Primary Lifecycle

Default to this lifecycle unless the user explicitly asks for a low-level workflow:

1. status

   • use selftune status
   • for draft packages, use selftune create status --skill-path <path>

2. verify

   • use selftune verify --skill-path <path>
   • if verify reports missing readiness or evidence, follow the returned next low-level command instead of rerunning the full chain

3. publish

   • for draft packages, use selftune publish --skill-path <path>
   • for already-live skills, publish usually means a validated Improve action plus Watch

4. improve

   • use selftune improve --skill <name> --skill-path <path>
   • let --scope auto choose bounded package search automatically when the skill already has package evidence or a draft package manifest
   • set --scope description|routing|body|package when the measured gap is already clear and you want to force the mutation surface
   • use --scope package when the problem spans routing and body together or you want measured frontier comparison before deciding what to publish
   • omit --dry-run when you want the winning package candidate promoted back into the draft automatically

5. run

   • use selftune run

Treat eval generate, unit-test, replay, baseline, watch, and body-specific evolution as advanced supporting workflows unless the user asks for them directly or the default lifecycle fails.

Command Execution Policy

selftune <command> [options]

Commands vary in output format:

• JSON by default: selftune doctor and selftune watch emit structured JSON on stdout.
• Text by default: selftune status, selftune last, selftune verify, selftune publish, and selftune improve print human-readable text when stdout is a TTY.
• Mixed runtime output: selftune run / selftune orchestrate emit JSON on stdout and a human report on stderr.
• JSON opt-in: selftune sync --json enables structured JSON output.
• Server: selftune dashboard starts a local SPA server — it does not emit data.

For health remediation, prefer machine-readable guidance.next_command or top-level next_command from selftune doctor output instead of inferring the next step from prose.

Run selftune <command> --help for exact flags. Read references/cli-quick-reference.md when you need the full flag reference.

Package Evaluation Pipeline (Creator Trust Loop)

When the user wants to improve a skill, default to this package evaluation pipeline before jumping straight to mutation. Each step builds measured evidence that the package is ready to publish:

• draft — the package exists but is still incomplete
• verify_blocked — the draft is still in one of the concrete readiness states: needs_spec_validation, needs_package_resources, needs_evals, needs_unit_tests, needs_routing_replay, or needs_baseline
• verified — the trust gates pass and the skill is ready to ship
• published — the skill was shipped successfully
• watching — post-deploy monitoring is active
• needs_improvement — measured evidence shows trigger, routing, body, or value gaps
• unhealthy — hooks, telemetry, config, or selftune itself is broken

If the user asks "how do I know this skill works?" or "can I trust this skill yet?", start with this pipeline, then use selftune status, the dashboard, or the skill report to explain what is still missing, whether the package is ready to publish, or whether it is already being watched live.

Workflow Routing

| Trigger keywords | Workflow | File | | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------- | --------------------------------- | | create skill, new skill package, author skill, bootstrap skill, scaffold package, benchmark report, package report, publish report | Create | workflows/Create.md | | verify skill, creator loop, can I trust this skill, how do I know this skill works, test this skill, ready to ship, ready to deploy | Verify | workflows/Verify.md | | publish skill, ship skill, deploy skill, go live, release skill | Publish | workflows/Publish.md | | search run, package frontier, candidate search, bounded package evolution, compare package candidates, optimize package, improve routing and body together, bounded evolution | SearchRun | workflows/SearchRun.md | | grade, score, evaluate, assess session, auto-grade | Grade | workflows/Grade.md | | evals, eval set, undertriggering, skill stats, eval generate | Evals | workflows/Evals.md | | improve, optimize skills, make skills better, triggers, catch more queries, apply proposal, apply contributor proposal | Improve | workflows/Improve.md | | evolve description, description-only evolution, improve trigger wording | Evolve | workflows/Evolve.md | | evolve body, evolve routing, full body evolution, rewrite skill, teacher student | EvolveBody | workflows/EvolveBody.md | | evolve rollback, undo, restore, revert evolution, go back, undo last change | Rollback | workflows/Rollback.md | | watch, monitor, regression, post-deploy, keep an eye on | Watch | workflows/Watch.md | | doctor, health, hooks, broken, diagnose, not working, something wrong | Doctor | workflows/Doctor.md | | ingest, import, codex logs, opencode, openclaw, pi, wrap codex | Ingest | workflows/Ingest.md | | replay, backfill, claude transcripts, historical sessions | Replay | workflows/Replay.md | | contributions, sharing preferences, opt in/out creator sharing, approve/revoke contributions | Contributions | workflows/Contributions.md | | creator contributions, selftune.contribute.json, enable/disable creator contribution | CreatorContributions | workflows/CreatorContributions.md | | signals dashboard, contributor signals, signals page, community dashboard, community data, contributor stats, signal health, how are signals, how is community | SignalsDashboard | workflows/SignalsDashboard.md | | contribute, share, export bundle, export data, anonymized, give back | Contribute | workflows/Contribute.md | | init, setup, set up, bootstrap, first time, install, configure selftune, alpha, enroll | Initialize | workflows/Initialize.md | | cron, schedule, automate evolution, run automatically | Cron | workflows/Cron.md | | schedule, selftune schedule, launchd, systemd, crontab, automation setup | Schedule | workflows/Schedule.md | | auto-activate, suggestions, activation rules, nag, why suggest | AutoActivation | workflows/AutoActivation.md | | dashboard, visual, open dashboard, show dashboard, serve dashboard | Dashboard | workflows/Dashboard.md | | evolution memory, session continuity, what happened last | EvolutionMemory | workflows/EvolutionMemory.md | | grade baseline, baseline lift, adds value, skill value, no-skill comparison | Baseline | workflows/Baseline.md | | eval unit-test, skill test, test skill, generate tests, run tests | UnitTest | workflows/UnitTest.md | | eval composability, co-occurrence, skill conflicts, family overlap, sibling confusion | Composability | workflows/Composability.md | | eval import, skillsbench, external evals, benchmark tasks | ImportSkillsBench | workflows/ImportSkillsBench.md | | telemetry, analytics, disable analytics, opt out, tracking, privacy | Telemetry | workflows/Telemetry.md | | orchestrate, autonomous, full loop, improve all skills, run selftune, run selftune loop, run with package search, automatic package improvement | Run | workflows/Run.md | | sync, refresh, source truth, rescan sessions | Sync | workflows/Sync.md | | badge, readme badge, skill badge, health badge | Badge | workflows/Badge.md | | workflows, discover workflows, scaffold workflow skill, build skill from logs | Workflows | workflows/Workflows.md | | alpha upload, upload data, send alpha data, manual upload | AlphaUpload | workflows/AlphaUpload.md | | recover, rebuild sqlite, recover db, legacy backfill | Recover | workflows/Recover.md | | quickstart, getting started, onboard, first time setup, new user | Quickstart | workflows/Quickstart.md | | uninstall, remove selftune, clean up, teardown | Uninstall | workflows/Uninstall.md | | repair, rebuild usage, fix skill usage, trustworthy usage | RepairSkillUsage | workflows/RepairSkillUsage.md | | export canonical, canonical export, canonical telemetry, push payload | ExportCanonical | workflows/ExportCanonical.md | | hook, run hook, invoke hook, manual hook, debug hook | Hook | workflows/Hook.md | | codex/opencode/cline/pi hooks, platform hooks, non-claude hooks, multi-agent | PlatformHooks | workflows/PlatformHooks.md | | registry, distribute, push/install/sync/rollback skill, team skills | Registry | workflows/Registry.md | | export, dump, jsonl, export sqlite, debug export | Export | (direct: selftune export) | | status, health summary, skill health, how are skills, run selftune | Status | (direct: selftune status) | | last, last session, recent session, what happened | Last | (direct: selftune last) |

Workflows Grade, Improve, Watch, and Ingest also run autonomously via selftune orchestrate. When package evaluation evidence exists, selftune orchestrate (aliased as selftune run) can automatically select package-level bounded search instead of description-level evolve.

Interactive Configuration

Before running mutating workflows (evolve, evolve-body, evals, baseline), consult references/interactive-config.md for the pre-flight configuration pattern, model tier reference, and quick-path rules.

Specialized Agents

selftune bundles focused agents in agents/. Read the relevant agent file and follow its instructions — either inline or by spawning a subagent.

| Trigger keywords | Agent file | When to use | | ---------------------------------------------------- | ------------------------------ | ------------------------------------------------------------ | | diagnose, root cause, why failing, debug performance | agents/diagnosis-analyst.md | Recurring low grades or unclear failures after doctor/status | | patterns, conflicts, cross-skill, overlap | agents/pattern-analyst.md | Skills overlap, misroute, or interfere | | review evolution, check proposal, safe to deploy | agents/evolution-reviewer.md | Before deploying high-stakes or marginal evolutions | | set up selftune, integrate, configure project | agents/integration-guide.md | Complex setup: monorepos, multi-skill, mixed-platform |

Advanced Workflows

Load these when the user explicitly asks for a low-level step, when the primary lifecycle fails, or when debugging needs deeper evidence:

• workflows/Evals.md
• workflows/UnitTest.md
• workflows/Baseline.md
• workflows/Replay.md
• workflows/Watch.md
• workflows/Evolve.md
• workflows/EvolveBody.md
• workflows/Composability.md
• workflows/ImportSkillsBench.md

Negative Examples

These should NOT trigger selftune — near-misses that share keywords:

• "Fix this React hydration bug" — general debugging, not skill improvement
• "Create a PowerPoint about Q3 results" — pptx skill, not selftune
• "Run my unit tests" — project tests, not skill eval tests
• "How do I use the Research skill?" — skill usage, not improvement
• "Generate a report from this data" — content generation, not skill evolution
• "My build is failing" — project issue, not selftune health
• "Evaluate this code for security issues" — code review, not session grading
• "Improve this function's performance" — code optimization, not skill optimization

The key distinction: selftune improves skills themselves (descriptions, triggers, execution quality). If the user wants to use a skill, route to that skill instead.

Creator-Directed Contribution

This skill ships a selftune.contribute.json config that enables creator-directed signal relay. When users install selftune and approve contribution, anonymous usage signals (trigger, grade, miss_category) are relayed to the selftune creator to improve the skill for everyone.

• The creator_id in the bundled config is the selftune creator's cloud user UUID.
• Users opt in via selftune contributions approve selftune.
• No raw session content is ever shared -- only privacy-safe aggregate signals.
• See workflows/CreatorContributions.md for creator-side setup.
• See workflows/Contributions.md for end-user opt-in/opt-out.

Routing keywords: creator contribution, selftune signals, dogfood relay, community contribution, signal sharing, opt in creator, creator UUID.

Additional References

Load these on demand — do not read unless needed for the current task:

| Reference | When to read | | ----------------------------------- | -------------------------------------------------------------------- | | references/cli-quick-reference.md | Need exact CLI flags beyond --help | | references/troubleshooting.md | Diagnosing common errors | | references/examples.md | Need step-by-step scenario walkthroughs | | references/creator-playbook.md | Publishing skills others install; before-ship vs after-ship pipeline | | references/interactive-config.md | Before mutating workflows | | references/grading-methodology.md | Grading sessions or interpreting grades | | references/invocation-taxonomy.md | Analyzing trigger coverage | | references/logs.md | Parsing or debugging log files | | references/setup-patterns.md | Complex platform-specific setup | | references/version-history.md | Checking what changed between versions | | settings_snippet.json | During initialization |