Agent skill

Autopilot

by aiblueprinthq in aiblueprinthq/ai-blueprint

Run one explicit bounded Blueprint spec and implementation pass through configured quality gates, then stop before completion or external actions.

MITAuto-check: warningsTesting & QA

Install Autopilot

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add aiblueprinthq/ai-blueprint --skill autopilot -a claude-code

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

GitHub CLI
$ gh skill install aiblueprinthq/ai-blueprint autopilot --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/aiblueprinthq/ai-blueprint.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/autopilot .claude/skills/autopilot && 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
autopilot
GitHub stars
463
Token cost
~4.4k tokens
SKILL.md length
2,475 words
Files
1
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

Run one explicit bounded Blueprint spec and implementation pass through configured quality gates, then stop before completion or external actions.

  • Works in 8 steps: preflight like /status → choose or write the spec → create or reuse the branch → …
  • Directly invokes /autopilot
  • SKILL.md covers Input, Step 1 - preflight like /status, Step 2 - choose or write the… and Step 3 - create or reuse the…, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Autopilot is an agent skill from aiblueprinthq/ai-blueprint. Run one explicit bounded Blueprint spec and implementation pass through configured quality gates, then stop before completion or external actions. Use only when the user directly invokes /autopilot, $autopilot, or asks for Autopilot.

Its SKILL.md is about 4.4k 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 Testing & QA, covering Quality gates. The repository describes itself as: A file-backed, spec-driven AI coding workflow framework for building real software while staying in control. The licence is MIT.

When your agent uses it

  • Directly invokes /autopilot
  • Asks for Autopilot

Example prompts

  • “/autopilot”

Workflow steps

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

  1. preflight like /status
  2. choose or write the spec
  3. create or reuse the branch
  4. implement in small steps
  5. configured acceptance check
  6. configured quality audit and repair
  7. configured try guide
  8. final review packet

What it can do on your machine

Read from SKILL.md and the folder at commit 96222b7. 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

    No scripts in the folder and no shell commands in SKILL.md.

    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

Autopilot loads about 4.4k tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 2,475 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~4.4k

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: warnings

The automated check found patterns that need a careful read before installing.

  • WarningTells the agent its actions are pre-authorized / not to stop for confirmationSKILL.md:142
    Do not pause for user approval after each passing step, regardless of the

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 aiblueprinthq/ai-blueprint at commit 96222b7, republished under its MIT licence (© aiblueprinthq). 2,475 words, ~4,432 tokens.

Download SKILL.mdSave it as .claude/skills/autopilot/SKILL.md (or your agent's skills folder).
name
autopilot
description
Run one explicit bounded Blueprint spec and implementation pass through configured quality gates, then stop before completion or external actions. Use only when the user directly invokes /autopilot, $autopilot, or asks for Autopilot.

autopilot - optional Blueprint loop

Context reuse: Reuse any required file already loaded in project instructions or the current session. Read it again only if absent, changed, or exact current bytes or line references are needed.

First action: Before project inspection, preflight, or any other tool call, publish running to blueprint/.state/run.json using the dashboard activity contract in AGENTS.md.

Where this sits in the workflow:

/status  ->  [autopilot]  ->  review packet  ->  /complete
(where       (spec, build,      (human review,    (log, commit,
 are we?)     configured gates)  fixes if needed)  merge with approval)

Autopilot is an explicit opt-in path. It uses the same Blueprint files and the same quality gates, but it does not stop after every normal review point. A single user request is permission to run one bounded loop until the feature is ready for review, blocked, or unsafe to continue.

It combines /feature or /fix with /implement and continues through the spec-review stop retained by the normal workflow. That human spec approval is the main control Autopilot intentionally removes. It does not remove the final review packet or the option to walk through the completed code.

It does not replace the normal workflow. /feature, /implement, /check, and /complete remain the conservative default.

Do not suggest Autopilot as the default next action. Use it only when the user explicitly asks for it.

The explicit Autopilot request is permission to create checkpoint commits on the feature or fix branch after passing implementation steps when workflow.checkpointCommits is enabled. It is not permission to merge, push, deploy, publish, send, delete data, or run destructive actions.

Input

Common forms:

  • No argument: resume the current feature if one exists, otherwise target the next unchecked build-plan item.
  • A number or name: target that build-plan feature, for example /autopilot 3 or $autopilot "directory listing".
  • fix "<issue>": write and build an ad-hoc fix spec.
  • resume: continue the current feature on its existing branch.

If the requested target conflicts with a feature already in progress, stop and ask which one should win. Do not overwrite blueprint/context/current-feature.md silently.

Rollback is intentionally excluded from Autopilot. If the request is a rollback or current-feature.md is marked Type: Rollback, stop and direct the user to the reviewed /implement path. Reversing completed work requires the explicit dependency and conflict gates in /rollback and /implement.

Step 1 - preflight like /status

Read the same state /status reads:

  • AGENTS.md
  • blueprint/config.json
  • blueprint/project-plan.md
  • blueprint/build-plan.md
  • blueprint/context/project-overview.md
  • blueprint/context/current-feature.md
  • blueprint/context/findings.md
  • blueprint/context/coding-standards.md
  • blueprint/context/ai-interaction.md
  • git branch, status, and recent log

Then decide whether it is safe to run.

Stop before changing files when:

  • blueprint/config.json exists but is invalid. Point the user to /doctor.
  • The repo is not a git repo.
  • The working tree is dirty and there is no current feature tying those changes to this run.
  • current-feature.md has real work and the user requested a different target.
  • project-overview.md is missing or stale and the planning docs are not clear enough to regenerate it.
  • The next feature is visual or replication-heavy and no design reference exists.
  • The task needs product, data, auth, billing, or destructive decisions the docs do not answer.

If the only issue is that project-overview.md is stale and the plans are clear, regenerate it using the /overview behavior and continue. Include that in the final packet.

The initial blueprint/.state/run.json record required by AGENTS.md must already show command autopilot and status running before preflight begins. After preflight passes, enrich it with boundary reviewed, the target feature or fix, and build-step progress when known. Update it after the spec, each passing build step, and each configured gate. On a hard stop, set status blocked with /autopilot resume when resuming is safe. At the final review packet, set status ready because Autopilot stops before /complete. Activity reporting must never weaken or block the workflow itself.

Step 2 - choose or write the spec

If blueprint/context/current-feature.md already contains an active spec, resume it. Read checked steps and continue from the first unchecked step.

If there is no active spec:

  1. Use the /feature behavior for a planned feature, or /fix behavior for a requested fix.
  2. Write blueprint/context/current-feature.md.
  3. Red-team the spec before building:
    • missing unhappy paths
    • oversized steps
    • undefined contracts
    • missing design reference
    • scope creep
    • vague done-whens
    • missing testing plan when AGENTS.md declares a test command
  4. Apply the spec fixes.

Autopilot may continue past this spec gate because the user explicitly invoked Autopilot. Still report what the critique changed in the final packet. Follow the proportional-engineering contract in AGENTS.md throughout this run.

Step 3 - create or reuse the branch

Use the same branch rules as /implement:

  • Feature: the configured feature prefix, default feature/<name>
  • Fix: the configured fix prefix, default fix/<name>

If the branch already exists, switch to it only if it matches the active spec. If switching branches would strand unrelated dirty work, stop and report the problem.

Step 4 - implement in small steps

Work through the spec's build steps in order. Each step must remain reviewable. Do not pause for user approval after each passing step, regardless of the configured workflow.stepReview value. The review happens at the final packet unless a hard stop is hit.

For every step:

  1. Implement only that step.
  2. Run the relevant verification:
    • the exact Verify command from AGENTS.md, when declared
    • otherwise the build, relevant test, lint, and typecheck commands already documented by the project
    • browser, CLI, API, or app-level evidence for behavioral done-whens
    • with verification.logicTests: "required", stop and point to /tests if logic changed but no test runner is configured
  3. If UI is involved, inspect the running app when possible. Prefer Playwright if it is already installed or declared. Capture screenshots when they add useful evidence. Check for console errors and failed requests. With verification.uiEvidence: "required", direct browser evidence is mandatory and unavailable evidence is a hard stop.
  4. Self-review the diff for the step:
    • does it match the spec?
    • did it add scope?
    • is the error path handled?
    • did it follow coding-standards.md?
    • are tests present for new in-scope logic when the test gate is on?
  5. Fix obvious issues and rerun the failed checks.
  6. Mark the step checked in current-feature.md only after the step passes.
  7. When workflow.checkpointCommits: "enabled", create a checkpoint commit on the feature or fix branch for the passing step. Include the code, tests, and the updated current-feature.md checkbox. Use a conventional message such as feat: checkpoint mock snapshot route or fix: checkpoint stale service filter. Keep the message about the step, not about Autopilot. When the value is disabled, leave the passing step uncommitted for the final review.

Do not batch the whole feature into one large diff. If a step gets too large, split the step in current-feature.md and continue with the first smaller step.

Step 5 - configured acceptance check

After all implementation steps are checked, apply qualityGates.regular.check:

  • manual - skip the automatic /check; it remains available when explicitly requested.
  • when-behavioral - run /check when a done-when needs observed runtime behavior such as a click, request, CLI command, download, background job, or multi-screen flow.
  • always - run /check for every work item.

After the required verification and configured Check gate pass, set the current spec's **Status:** to verified before any independent-review checkpoint. Audit findings and review state may still block completion. Leave the spec in progress, verification failed, or verification incomplete on any stop that lacks complete verification evidence.

For pure library or CLI work, build plus tests and representative command output may be enough. Be explicit about the evidence used.

Show full SKILL.md (1,252 more words)Show less

Step 6 - configured quality audit and repair

Apply qualityGates.regular.independentReview before a same-session audit:

  • manual skips automatic independent review unless a request already exists.
  • when-sensitive requires it for authentication, authorization, payments, secrets, personal or user data, migrations, destructive operations, external side effects, security boundaries, or unusually broad changes.
  • always requires it for every work item.

The selected review runs after all implementation steps, final Verify, required Check, and the verified spec, before the final review packet and /complete. review.independentExecution chooses the manual fresh-session handoff or an automatic isolated reviewer; it does not change when the gate is selected.

When selected, do not review the builder's work in this session. Ensure application code is in an approved clean checkpoint. Include the verified spec when tracked; an intentionally ignored spec uses Audit's local Spec snapshot contract without changing visibility. Then follow Phase A of /audit independent current. With automatic execution, spawn and wait for the isolated reviewer, then validate its normal receipt. With manual execution, stop with the handoff. Autopilot may use its existing configured checkpoint authority when checkpoint commits are enabled; otherwise show the exact review-checkpoint candidate and ask before committing. On resume, continue only when a fresh reviewer wrote a current passed receipt. Repair changes-requested P0/P1 findings within the normal scope and attempt limit, then obtain a new checkpoint and prepare a new review. A passing independent receipt satisfies the configured Audit gate. A local-spec-only revision may reuse the same approved product HEAD after normal spec and verification gates, with a new snapshot/request and full fresh review. Do not create an empty commit for ignored spec changes. Automatic execution must also confirm access to the same local spec/snapshot and installed skills; otherwise retain the request and use the manual handoff in the original checkout.

The request records Requested execution; the receipt records Actual execution. Require the execution and reviewer-context pairing defined by the project-local review contract, including actual manual plus fresh session when an automatic request explicitly falls back. On resume, a pending request without Requested execution is legacy manual-only. Never add execution fields or run a subagent against it.

Apply qualityGates.regular.audit:

  • manual - skip the automatic audit; /audit remains available when explicitly requested.
  • when-sensitive - run /audit current for authentication, authorization, payments, secrets, personal or user data, migrations, destructive operations, external side effects, security boundaries, or unusually broad changes.
  • always - run /audit current for every work item.

When the gate runs, audit the active feature, its diff, and the nearby code affected by the change. This is a targeted feature audit, not a repository-wide cleanup pass. Findings are recorded in blueprint/context/findings.md with durable IDs and statuses, as /audit defines; the ledger reports status and never scopes what the audit examines.

For every finding:

  1. Validate it against the actual code, spec, tests, coding-standards.md, and local project patterns. An audit finding is evidence to investigate, not an automatic instruction to edit.
  2. Repair confirmed P0 and P1 findings when the fix stays inside the approved feature scope, does not require a product or architecture decision, and does not remove or change shipped behavior. Set the repaired finding to fixed in the ledger, never closed.
  3. Report P2 and P3 findings in the final packet. Fix them only when the change is small, directly caused by the current feature, and clearly required by the project standards.
  4. If a confirmed P0 or P1 finding cannot be repaired safely within scope, stop and report it. Do not present the feature as ready for /complete.

After any audit repair:

  1. Rerun the documented Verify command when present; otherwise rerun the affected build, lint, typecheck, and test commands.
  2. Rerun the acceptance evidence affected by the repair.
  3. Recheck the repaired area using the same targeted audit criteria. When that recheck confirms the original defect is gone and the repair introduced no new one, move the fixed finding to closed under the /audit close conditions and name it in the packet. An unrelated new finding gets its own ledger entry and does not keep the repaired one open.
  4. Create a checkpoint commit only after the repair and its checks pass, and only when checkpoint commits are enabled.

Use the existing two-attempt hard stop for repeated repair failures. Do not widen the feature into a general refactor, silently suppress a finding, or turn this step into a full-project hardening pass. A broader cleanup remains a separate /audit followed by planned /fix work.

Step 7 - configured try guide

Apply qualityGates.regular.tryGuide:

  • manual - skip automatic generation; /check guide remains available when explicitly requested.
  • when-user-facing - run /check guide when the change affects UI, navigation, copy, a public API or CLI, output, or another workflow a person directly uses.
  • always - generate a guide for every work item.

The guide is a review artifact, not proof. Never claim the user performed it.

Step 8 - final review packet

Stop with a concise review packet. Keep it useful enough for /complete but not a full audit report:

  • branch name
  • target feature or fix
  • whether the spec was created or resumed
  • what the spec critique changed
  • changed files and why each changed
  • build/test/check commands run, with pass or fail
  • effective regular quality-gate policies and which automatic gates ran or were skipped
  • independent-review target, selected reviewer and model, and receipt state
  • screenshots or output paths, when relevant
  • how to try it manually, or a pointer to /check guide for the full walkthrough
  • checkpoint commits created
  • self-review findings
  • targeted audit scope and findings, when the audit gate ran
  • audit repairs made and checks rerun, when applicable
  • P0/P1 findings still open or fixed in blueprint/context/findings.md, which block /complete
  • unresolved risks or skipped checks
  • exact next action

If everything is green, the next action is usually: review the diff, run /check guide if its gate was manual and a walkthrough is wanted, then /complete.

Always offer a read-only walkthrough of the completed code after the packet. Follow the spec's build steps, explain the key files, symbols, flow, and non-obvious decisions, then offer a focused deep dive. Keep /check guide distinct as the manual product-review path.

If something failed, name the failing check and the next fix target.

Hard Stops

Stop immediately and report instead of continuing when Autopilot would need to:

  • commit on main, merge, delete a branch, push, deploy, publish, or send anything
  • delete data, reset a database, run irreversible migrations, kill processes, or change system settings
  • install dependencies or use network access without the current tool's approval flow
  • make a product decision not covered by the docs
  • continue after two failed fix attempts on the same issue
  • hide, skip, or hand-wave a failing check

Rules

  • One Autopilot run handles one feature or one fix.
  • Autopilot creates checkpoint commits on the feature or fix branch after passing steps only when project config enables them.
  • Autopilot uses qualityGates.regular. The Continuous gate policies and the continuous section do not change an Autopilot run.
  • When its audit gate runs, Autopilot audits the active feature and affected code, not the entire project.
  • A P0 or P1 finding left open or fixed in blueprint/context/findings.md blocks readiness for /complete. The ledger is what makes this enforceable.
  • Autopilot stops before /complete. It never merges.
  • The Blueprint files remain the state machine. Keep current-feature.md accurate as steps complete.
  • Follow coding-standards.md, ai-interaction.md, and AGENTS.md.
  • Prefer fewer, higher-quality changes over broad coverage.
  • Report uncertainty plainly. A blocked run is useful if it tells the truth.

Formatting

Format the output to match the project's conventions in blueprint/context/ai-interaction.md: concise, scannable markdown, with lists for enumerations and tables for matrices rather than dense paragraphs.

© aiblueprinthq, MIT. 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/autopilot of aiblueprinthq/ai-blueprint.

Open the folder on GitHubat commit 96222b7

Compare with similar skills

Autopilot 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.

Autopilot compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Autopilot this skillaiblueprinthq/ai-blueprint463—~4.4kAutomated safety check: WarnMIT
Feature Plannerserendipity1004/cc-feature-implementer176—~2.4kAutomated safety check: PassNone
Ccg Workflowfengshao1227/ccg-workflow5.9k—~2.3kAutomated safety check: PassMIT
Conducty Checkpointrobertbarclayy/conducty176—~1.5kAutomated safety check: PassMIT
Mission Plannerjdforsythe/forge151—~3.5kAutomated safety check: PassMIT
Quality Gate0xNyk/lacp305—~382Automated safety check: PassMIT

Similar skills

  • Feature Planner

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    176 GitHub stars~2.4k tokensUpdated 9 mo ago
    Testing & QAAuto-check passed
  • Ccg Workflow

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Categories

Questions about Autopilot

What does Autopilot do?

Run one explicit bounded Blueprint spec and implementation pass through configured quality gates, then stop before completion or external actions. Autopilot is an agent skill from aiblueprinthq/ai-blueprint. Run one explicit bounded Blueprint spec and implementation pass through configured quality gates, then stop before completion or external actions.

When should I use Autopilot?

Autopilot fits situations like: directly invokes /autopilot; asks for Autopilot.

How do I install Autopilot in Claude Code?

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

How do I install Autopilot in Codex?

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

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

What does Autopilot need to run?

SKILL.md names no scripts, command-line tools or credentials: Autopilot is instructions for the agent only.

Does Autopilot 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 Autopilot safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): tells the agent its actions are pre-authorized / not to stop for confirmation. Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Autopilot use?

Autopilot is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Autopilot use?

About 4.4k tokens (SKILL.md is roughly 18k 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 Autopilot?

Skills that share tags, products or a category with Autopilot: Feature Planner (serendipity1004/cc-feature-implementer, 176 stars), Ccg Workflow (fengshao1227/ccg-workflow, 5.9k stars), Conducty Checkpoint (robertbarclayy/conducty, 176 stars) and Mission Planner (jdforsythe/forge, 151 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Autopilot?

aiblueprinthq (a GitHub organization) maintains it in aiblueprinthq/ai-blueprint, which has 463 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on October 8, 2026.

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