Autonomous Maintainer

Autonomous Maintainer

Turn the agent into an autonomous maintainer: set the product up once, then run a loop of small, self-contained changes — each one made, committed, verified, and kept or reverted — logging every experiment. Production stays deployable the whole time. "Better" is defined by real user need, not cosmetic churn.

For a single scoped change with a finish line (a migration, one feature), this is the wrong shape — that's a finite task, not a forever loop. Use it only when the goal is ongoing improvement.

Setup (once, with the user)

1. Core product & intent — what it does, who uses it, and what "better" means for them.

This is the yardstick every later change is judged against.

1. Codebase & platform — where the code lives, where it runs (Vercel / Railway /

self-hosted), and the exact build / run / test / deploy commands.

1. Read the whole codebase — take notes on what affects what; know the surface before you

touch it.

1. Baseline — confirm it builds, runs, deploys cleanly as-is, and that you can

reproduce current behavior, before changing anything.

1. Init changelog.md — one terse entry per experiment (date, change, why, keep/revert,

how verified). Never log secrets or user data.

1. Confirm and go — get the user's OK on the above, then start the loop.

Can / cannot

• CAN modify anything that ships to users: application code, components, styles, config,

content.

• CANNOT, without the user's explicit OK:
• Change the product's core purpose or remove functionality users depend on.
• Take destructive or hard-to-reverse production actions — deleting or migrating user data,

dropping tables, deleting accounts, rotating credentials.

• Break the build or deploy. Every kept change leaves the product working and deployable.

The loop (until interrupted)

Work on a dedicated branch; keep main/production deployable at every commit.

1. Assess — branch/commit, current behavior, known issues.
2. Pick the highest-value change available now — biggest user benefit, or biggest risk to

retire.

1. Make it. Prefer small, verifiable changes; a bigger one is fine only when the payoff is

real. Simpler is better — deleting code for equal/better behavior always wins.

1. Commit (use the commit skill for the message).
2. Verify (below).
3. Keep or revert. Keep only a genuine, verified improvement; advance the branch (deploy

if confident and the workflow calls for it, else leave it for the user to ship via ship). Otherwise — worse, neutral-but-more-complex, or broken — git reset back.

1. Log the outcome in changelog.md.

Verifying a change

You are the evaluator. Before keeping anything:

• Build — it compiles, no errors.
• Checks — run the project's tests, lint, typecheck (e.g. make all, bun lint,

bun typecheck). This is ground truth. (See the verify skill for driving the real flow.)

• Run it — exercise the change end-to-end; confirm it does what you intended and breaks

nothing adjacent.

• Analytics (if wired) — after it settles, confirm the relevant events/funnels/errors move

the intended way with no regression.

A change is good only if the product still works end-to-end and does what you intended. If you can't verify it, treat it as not working.

Analytics (optional)

If the product has PostHog or similar, use it both to choose work and to confirm impact — pair with the posthog skill. Instrument missing signal yourself (tracking a missing user action is a valid experiment). Let funnels, drop-offs, errors, and retention pick the highest-value work. Gate risky changes behind feature flags. Never put PII or secrets in event properties.

Never stop

Once the loop begins, don't ask the human whether to continue — they may be away and expect work until manually stopped. Out of ideas? Re-read the codebase for rough edges, mine analytics for real user pain, polish UX, pay down tech debt, improve tests and docs, try bolder features. To actually run unattended, drive the loop with the loop skill (a recurring interval) and let it run until interrupted. Left running, it stacks up many verified, logged improvements — the user returns to a maintained, better product.

Guardrails

• Keep main/production deployable at all times; do experiments on a branch.
• Never fake green — don't weaken, skip, or delete tests to pass.
• Rewind sparingly: quick breakage (typo, bad import) → fix and re-verify; fundamentally

broken or fighting you after a few tries → revert, log it, move on.

• Never log secrets or user data in changelog.md or analytics.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: therapys
• Source: therapys/dotagents
• License: MIT

Install and usage instructions live in the source repository linked above.