Agent skill

Auto

by udecode in udecode/kitcn

Autonomous kitcn supervisor for sweep, clean, full, design, milestone, PRD, timed, and review-until work.

Apache-2.0Auto-check passedProduct & Project Management

Install Auto

skills CLI
$ npx skills add udecode/kitcn --skill auto -a claude-code

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

GitHub CLI
$ gh skill install udecode/kitcn auto --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/udecode/kitcn.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/auto .claude/skills/auto && 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
auto
GitHub stars
450
Token cost
~4.7k tokens
SKILL.md length
2,274 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
Apache-2.0

At a glance

Autonomous kitcn supervisor for sweep, clean, full, design, milestone, PRD, timed, and review-until work.

  • Works in 7 steps: VISION.md, docs/README.md, and the named… → The active plan/PRD/milestone and… → Exact public exports, runtime entries,… → …
  • Tasks that involve PRD writing
  • SKILL.md covers Core Take, Modes, Front-Door Routing and Run Profile Compiler, plus 22 more sections
  • Calls bun, node and npx

What it does

Auto is an agent skill from udecode/kitcn. Autonomous kitcn supervisor for sweep, clean, full, design, milestone, PRD, timed, and review-until work. Compiles a run profile, keeps evidence-backed state, decomposes local task packets, repairs its workflow, and closes through GitHub delivery.

Its SKILL.md is about 4.7k 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 PRD writing and Project management. It works with GitHub. The repository describes itself as: Convex + Better Auth + tRPC + Drizzle + TanStack Query + shadcn. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve PRD writing
  • Tasks that involve Project management

Example prompts

  • “/auto”

Workflow steps

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

  1. VISION.md, docs/README.md, and the named local source.
  2. The active plan/PRD/milestone and unresolved decisions.
  3. Exact public exports, runtime entries, package manifests, and call sites.
  4. Tests/fixtures/scenarios that define the current behavior.
  5. CLI/template/generated owners when scaffold output is involved.
  6. Matching docs and packages/kitcn/skills/kitcn/** when user guidance moves.
  7. Local OSS clones for unfamiliar or parity-sensitive API design.

What it can do on your machine

Read from SKILL.md and the folder at commit c6010f5. 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:

    • bun
    • node
    • npx

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

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    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

Auto loads about 4.7k tokens when it runs. Until then it costs about 63 tokens; SKILL.md has 2,274 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~63
When it runs · the whole SKILL.md, loaded when a task matches
~4.7k

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 udecode/kitcn at commit c6010f5, republished under its Apache-2.0 licence (© udecode). 2,274 words, ~4,700 tokens.

Download SKILL.mdSave it as .claude/skills/auto/SKILL.md (or your agent's skills folder).
name
auto
description
Autonomous kitcn supervisor for sweep, clean, full, design, milestone, PRD, timed, and review-until work. Compiles a run profile, keeps evidence-backed state, decomposes local task packets, repairs its workflow, and closes through GitHub delivery.
argument-hint
<feature | source path | current tree> [sweep|clean|full|design|milestone|prd|timed <duration>|autoreview-until <P1|P2|P3|clean>]

Auto

Auto is the front door when the user wants the repository to keep choosing and executing the next safe owner without repeated prompting.

Core Take

Auto is a supervisor, not a larger implementation skill. It compiles the run, records durable state, selects the next checkpoint from evidence, invokes the real owner, verifies the result, and continues until the auditable stop condition is true.

Before the first file mutation, capture a walkthrough diff baseline when UI or rendered output may change. Use .agents/skills/walkthrough/scripts/diff-baseline.mjs and record its path.

The loop is:

text
request -> run profile -> vision/source intake -> readiness
-> candidate owner -> execute -> proof -> state update -> next candidate
-> review -> repository gate -> GitHub delivery -> final audit

Do not score the entire run up front. Score only when more than one valid next checkpoint exists.

Modes

ModeContract
sweepFind and complete the highest-value safe improvements in the named boundary; do not create a new PRD by default.
cleanClose the current tree through proof, sync, review, checks, and GitHub delivery; route execution to autoclosure.
fullConsume a named capability, source, or best relevant local PRD; decompose directly into local task packets; implement, verify, sync docs/skills, review, and complete the GitHub PR path.
designRoute through design, implement when requested, and prove the live surface.
milestoneRoute through to-milestone; terminal unless another mode is also named.
prdRoute through to-prd; terminal unless full is also named.
timed <duration>Repeat useful bounded loops until the timebox ends, preserving a safe closeout reserve.
autoreview-until <threshold>Run fresh review rounds, repair accepted findings, and stop at the named clean/P-level threshold or a hard blocker.

A bare feature plus full may use an existing local PRD when useful. If no PRD is required to make coherent decisions, Auto writes the decisions and packets in its goal plan instead of creating planning ceremony.

Front-Door Routing

EvidenceOwner
fuzzy failure or flaky regressiondiagnosing-bugs
ordinary bounded implementationtask
architecture, migration, benchmark, or public-API proposalmajor-task
hard removalhard-cut
structural ownership cleanuparchitecture-cleanup
live behavior change suited to red-green-refactortdd, then task owner
UI route/component designdesign
doctrine contradiction or driftvision / sync-vision
unclear directiongrill-with-vision
milestone mapto-milestone
implementation-ready capability sourceto-prd
working tree closeoutautoclosure
final code reviewautoreview

Use orchestrator only when the user explicitly requests parallel child thread/branch work. Auto never invents parallel delegation or worktrees.

Run Profile Compiler

Before work, compile and record this profile in the goal plan:

FieldValues / meaning
sourceprompt, PRD, milestone, plan, paths, current tree
modeone primary mode plus modifiers
targetrequested outcome in one sentence
boundaryincluded paths/surfaces and explicit exclusions
architecture depthordinary, cleanup, or major
behavior strategyinspect, reproduce, TDD, migrate, remove
proof harnessunit, integration, type/build, fixture, scenario, Browser, benchmark, exact-term audit
docs/generatedowners and regeneration commands
deliverylocal-only or GitHub PR path
parallelismoff unless user explicitly requested it
review thresholdnormal, P3, P2, P1, or clean
timeboxnone or duration plus closeout reserve
stop conditionmeasurable completion or hard blocker

Reject impossible combinations instead of silently weakening one. full cannot become planning-only because a PRD was created. clean cannot expand into a new feature. A timed run cannot spend its closeout reserve on new scope.

Goal Plan Contract

Use autogoal before durable Auto work. Create or resume a plan from the auto template with the agent-native pack and any relevant browser, design, docs, package-api, release, or to-prd pack.

The plan must contain:

  • run profile and source inventory;
  • completion threshold and explicit exclusions;
  • state capsule;
  • decision, assumption, claim, error-attempt, and packet ledgers;
  • readiness and proof matrices;
  • source/generated owner map;
  • review, repository-check, and delivery gates;
  • phase states and completion audit.

Checkpoints are receipts. Update the plan after meaningful execution, not only at the end.

Before full closeout, run both plan validators:

bash
node .agents/rules/auto/scripts/check-plan-placeholders.mjs <plan-path>
node .agents/skills/autogoal/scripts/check-complete.mjs <plan-path>

The placeholder audit fails unresolved TODO/TBD text, bare pending cells, and unchecked items. The autogoal checker proves the resolved goal-plan structure.

State Capsule

Keep this compact capsule current so work can resume without rereading the world:

text
mode:
target:
active source:
active packet:
current owner:
last proven fact:
latest changed files:
next proof:
open blocker:
decision debt:
time remaining / reserve:

Update after source changes, failed proof, owner changes, and packet closeout. Never claim a state that is only planned.

Source Intake

Read only what can change the next decision:

  1. VISION.md, docs/README.md, and the named local source.
  2. The active plan/PRD/milestone and unresolved decisions.
  3. Exact public exports, runtime entries, package manifests, and call sites.
  4. Tests/fixtures/scenarios that define the current behavior.
  5. CLI/template/generated owners when scaffold output is involved.
  6. Matching docs and packages/kitcn/skills/kitcn/** when user guidance moves.
  7. Local OSS clones for unfamiliar or parity-sensitive API design.

Build a source-backed case matrix rather than reading broad directories without a question.

Full Mode Contract

auto full is terminal only when every applicable lane is proven:

  1. Resolve the named source or the latest relevant unfinished local PRD.
  2. Repair bounded contradictions, placeholders, missing owner decisions, and weak proof contracts in that source.
  3. If the source is fundamentally missing, route once to to-prd; then return to the same full run.
  4. Decompose directly into local task packets in the PRD or active Auto plan.
  5. Execute each packet with task, major-task, architecture-cleanup, hard-cut, design, or tdd as its true owner.
  6. Run package build, changeset, fixture, scenario, docs/package-skill, browser, and generated-output gates required by the changed surface.
  7. Run final cleanup and reviews.
  8. Run bun lint:fix and bun check.
  9. Commit, push, and open/update the GitHub PR when the run includes verified code-changing delivery.
  10. Audit the complete goal plan and close the durable goal.

Local PRDs and task packets own decomposition; the GitHub PR owns delivery and review.

Task Packet Ledger

Every implementation packet gets one row:

PacketOutcomeOwner/filesDepends onConflict groupModeAcceptanceProofStatus

Mode is one of:

  • blocking: must close before dependent packets;
  • parallel-join: may overlap only when explicit parallel work is authorized, but joins before its claim is consumed;
  • detached: useful but cannot change the requested completion claim.

Consolidate test-only, docs-only, guard-only, and refactor-only fragments into the behavior packet they support unless ownership and acceptance are truly independent.

Claim Receipts

Any important final claim must have a receipt:

ClaimExact evidenceFreshnessScopeConfidenceStatus

Allowed evidence includes source lines, test output, generated diffs, runtime observations, Browser proof, benchmark results, package exports, build artifacts, and authoritative external docs. A plan checkbox or command exit code without relevant assertions is not enough.

For evidence-backed claims:

  • high: direct fresh evidence covers the exact claim and boundary;
  • medium: direct evidence plus a bounded inference;
  • low: unverified inference, stale evidence, or incomplete boundary.

Completion claims require high confidence. Rewrite, narrow, or keep working when confidence is lower.

Hard Confidence Thresholds

These block progress regardless of candidate score:

GateMinimumIf below
public API/type contractexact source and compile/test proofinspect or redesign
auth/session/permission flowowner and denied-path proofstop implementation claim
Convex entry import graphexact static graph for changed entrysplit imports/owner
generated ownershipsource + regeneration + representative diffrepair owner
package behaviorfocused tests + package buildfix before broader check
scaffold/fixture behaviorsource regeneration + fixture checkregenerate/repair
docs/package skillpaired current-state auditsynchronize
UI behaviorstate matrix + Browser proofimplement/prove
GitHub deliverycommit/PR/check state read-backkeep delivery open

Decision Debt Cap

Decision debt is an unresolved choice that can change public behavior, owner boundaries, security, data lifecycle, or proof. Keep at most three active items and none on the critical path to the active packet.

DecisionWhy unresolvedRecommended answerEvidence neededDeadline

If the cap is exceeded, stop implementation and resolve the highest-impact decision. Cosmetic preferences do not count.

Assumption Ledger

AssumptionEvidenceRisk if falseValidationStatus

Validate high-impact assumptions before code. Low-impact reversible assumptions may proceed if they are explicit and tested before closeout.

Readiness Ownership

One owner signs each readiness lane:

LaneOwnerReady means
product/doctrinevision/PRDoutcome and non-goals are settled
public APIpackage ownernames/types/errors/hard cut are settled
runtime/data/authimplementation ownerentry, data, identity, and denial flow are mapped
generated/scaffoldsource ownerregeneration and representative output are known
prooftask ownercase matrix and harness can prove acceptance
docs/skilldocs ownercurrent-state docs and package skill have matching scope
deliveryAuto parentreviews/checks/GitHub path are explicit

Do not let multiple scorecards create fake rigor. Use readiness ownership to answer who must act next.

Show full SKILL.md (931 more words)Show less

Scenario And Proof Matrix

Create a row for every source-listed behavior and failure class:

ScenarioEntry/inputExpected behaviorHarnessEvidenceStatus

Include, when applicable:

  • happy path and empty/missing input;
  • auth/session/permission denial;
  • validation and typed error behavior;
  • retry/idempotency/concurrency;
  • live subscription and non-live cache behavior;
  • package export and consumer type flow;
  • CLI interactive, --yes, and --json behavior;
  • scaffold regeneration and fixture diff;
  • Convex bundle/import boundary;
  • UI loading, error, permission, responsive, and keyboard behavior;
  • deletion/absence of superseded APIs for a hard cut.

Every row is pass, blocked with evidence, or N/A with reason.

Harness Selection

Choose the smallest harness that can disprove the claim:

NeedHarness
pure behaviorfocused unit test
cross-module contractintegration test
public types/exportssource-first typecheck and package build
generated templategenerator + fixture check
end-to-end exampleprepared scenario, never committed fixture in place
UI/runtimedev server + Browser
performance/sizerepeatable benchmark or bundle graph
agent workflowhelper smoke, source/mirror audit, placeholder gate

Record command, cwd, prerequisites, expected signal, actual result, and artifact.

Error-Attempt Ledger And Self-Repair

For any repeated failure record:

AttemptFailure signatureHypothesisDifferent moveResult

After two attempts with the same signature, stop repeating the command. Change the diagnostic layer: reduce the repro, inspect ownership, refresh dependencies once when the failure shape indicates environment rot, switch harness, or route to diagnosing-bugs.

Trigger workflow self-repair when:

  • the run repeatedly chooses the wrong skill;
  • a required receipt cannot be represented in the plan;
  • generated sources drift after the documented command;
  • a stop rule permits false completion;
  • an error recurs because the workflow gives no next-different move.

Repair the smallest source-owned rule/template/helper, add a smoke or eval case, regenerate mirrors, and run agent-native-reviewer plus autoreview. Do not rewrite the workflow merely because one task was awkward.

Skill Evaluation

For every changed skill keep at least one evaluation row:

Prompt/caseExpected routeRequired receiptsForbidden behaviorResult

Evaluate routing, placeholder failure, completion pass, source/generated ownership, and omitted workflows. A description that reads well is not proof that the skill routes correctly.

Candidate Scoring

When more than one safe next checkpoint exists, score 0-5:

  • user/developer leverage;
  • vision fit;
  • unblock value;
  • evidence strength;
  • proof availability;
  • reversibility;
  • deletion/complexity reduction;
  • conflict risk (reverse scored).

Record the top candidates, selected owner, and rejected high-scoring candidate with reason. If one owner is obvious, write no score needed.

Self-Grilling

Before an irreversible design or before full closeout, ask:

  • Does this preserve kitcn's familiar mental models?
  • Is the type path end to end or locally simulated?
  • Is the Convex function bundle as narrow as the operation?
  • Is the public surface smaller and clearer than the alternatives?
  • Are CLI and generated ownership deterministic for agents?
  • Does auth fail closed at the real owner?
  • Are docs written for the current state?
  • Can every acceptance claim be disproved by the selected harness?
  • What attractive extra scope should be cut?

Record answers and changed decisions, not rhetorical questions.

Timed Loops

For timed <duration>:

  1. Reserve at least 20% of the timebox for proof, review, and handoff.
  2. Select packets small enough to finish before that reserve.
  3. At each checkpoint update time remaining, active packet, and safe stop.
  4. When reserve begins, stop opening scope and enter autoclosure.
  5. A timebox ending is not completion; report proven work and the exact next packet or blocker.

Waits are work only when an external process is expected to change. While a safe independent packet exists, do it rather than polling.

Review-Until

Each review round must be fresh and independent:

  1. Snapshot the intended delta and proof.
  2. Run the selected reviewer without priming it with the prior verdict.
  3. Classify findings: accept, reject with source evidence, or duplicate.
  4. Fix accepted findings and rerun targeted proof.
  5. Continue until the named threshold is met or the capped rounds expose a hard unresolved risk.

Never weaken full because the requested review threshold is lower. Final autoreview is still mandatory.

All-Lane Closeout

Before completion score each applicable lane 0-100 with evidence:

LaneAppliesScoreEvidenceNext owner if below 95
source/decision readinessyes/no
implementation/public APIyes/no
data/auth/bundle ownershipyes/no
tests/fixtures/scenariosyes/no
docs/package skill/generatedyes/no
UI/runtime proofyes/no
cleanup/reviewyes/no
checks/GitHub deliveryyes/no
goal audityes

No applicable lane below 95 may be called complete. Use N/A only with a specific boundary reason. The score points to the next owner; it never replaces the receipt.

Command Discipline

  • Use repository scripts and exact working directories.
  • Prefer focused proof before broad gates.
  • Do not run committed fixtures in place; prepare scenarios under tmp.
  • Run bun install once when the task or dependency state requires it.
  • Keep package behavior source-first; build for artifacts/exports or packages that intentionally require it.
  • Edit .agents and package skill sources, never generated mirrors.
  • Manage installed skills only through npx skills add/update/remove.
  • Run bun install after source/lock changes to regenerate agent output.
  • For authorized GitHub delivery, follow repository branch/check/whole-checkout rules exactly.

Stop Rules

Stop only when:

  • the measurable target and all applicable lanes are proven;
  • a missing user/external authority action blocks the next safe move;
  • an irreversible decision outside the source contract requires direction;
  • repeated different diagnostics prove an environment blocker;
  • the timed closeout boundary is reached with a truthful partial handoff.

Do not stop because a plan, PRD, packet list, code diff, test pass, reviewer verdict, commit, or PR exists. None alone proves the full run.

Final Handoff

Report outcome first, then:

  • source and packets completed;
  • key behavior/public API decisions;
  • proof and repository gates;
  • annotated walkthrough images when UI or rendered output changed;
  • generated/docs/package-skill sync;
  • review findings resolved or rejected with evidence;
  • GitHub PR/check state;
  • residual risks, waivers, or exact blocker;
  • final goal-plan audit and durable goal status.

© udecode, Apache-2.0. 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 .agents/skills/auto of udecode/kitcn.

Open the folder on GitHubat commit c6010f5

Compare with similar skills

Auto 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.

Auto compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Auto this skilludecode/kitcn450—~4.7kAutomated safety check: PassApache-2.0
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT
Notion Pmborghei/Claude-Skills874—~1.7kAutomated safety check: PassMIT
Ouroboros PM InterviewQ00/ouroboros6.2k—~5.7kAutomated safety check: PassMIT
Project Managerpwrdrvr/openclaw-codex-app-server265—~1.5kAutomated safety check: PassMIT
To Issuessmallnest/pigo474—~1.9kAutomated safety check: PassMIT

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Works with

Questions about Auto

What does Auto do?

Autonomous kitcn supervisor for sweep, clean, full, design, milestone, PRD, timed, and review-until work. Auto is an agent skill from udecode/kitcn. Autonomous kitcn supervisor for sweep, clean, full, design, milestone, PRD, timed, and review-until work.

When should I use Auto?

Auto fits situations like: tasks that involve PRD writing; tasks that involve Project management.

How do I install Auto in Claude Code?

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

How do I install Auto in Codex?

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

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

What does Auto need to run?

Going by SKILL.md and its folder, Auto needs the command-line tools its instructions call (bun, node and npx).

Does Auto access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Auto 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 Auto use?

Auto is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Auto use?

About 4.7k tokens (SKILL.md is roughly 19k 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 Auto?

Skills that share tags, products or a category with Auto: CCPM Project Management (automazeio/ccpm, 8.4k stars), Notion Pm (borghei/Claude-Skills, 874 stars), Ouroboros PM Interview (Q00/ouroboros, 6.2k stars) and Project Manager (pwrdrvr/openclaw-codex-app-server, 265 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Auto?

udecode (a GitHub organization) maintains it in udecode/kitcn, which has 450 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 1, 2026.

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