Agent skill

Autonomous Dev

by softspark in softspark/ai-toolkit

Drives a brief, specification, issue or existing PR through implementation, review, tests and QA to a ready PR.

Apache-2.0Auto-check: notes

Install Autonomous Dev

skills CLI
$ npx skills add softspark/ai-toolkit --skill autonomous-dev -a claude-code

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

GitHub CLI
$ gh skill install softspark/ai-toolkit autonomous-dev --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/softspark/ai-toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/app/skills/autonomous-dev .claude/skills/autonomous-dev && 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
autonomous-dev
GitHub stars
179
Token cost
~2.6k tokens
SKILL.md length
1,262 words
Files
8 (incl. scripts)
Skills in repo
112
Repo updated
First seen
Licence
Apache-2.0

At a glance

Drives a brief, specification, issue or existing PR through implementation, review, tests and QA to a ready PR.

  • Works in 7 steps: Discover and claim. Resolve the source… → Plan. Map each acceptance criterion to… → Implement. Use the relevant development… → …
  • Autonomous software delivery
  • SKILL.md covers Entry points, Setup and authorization, Durable state and Delivery process, plus 4 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Autonomous Dev is an agent skill from softspark/ai-toolkit. Drives a brief, specification, issue or existing PR through implementation, review, tests and QA to a ready PR. Persists ownership, progress and commit-bound evidence for safe resumption. Use for autonomous software delivery or finishing an interrupted development run.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts (for example `reference/process.md`, `reference/project-config.md` and `reference/run-state.md`).

The repository describes itself as: Professional-grade AI coding toolkit: 94 skills, 44 agents, multi-platform (Claude, Cursor, Windsurf, Copilot, Gemini, Cline, Roo Code, Aider, Augment, Antigravity, Codex CLI… The licence is Apache-2.0.

When your agent uses it

  • Autonomous software delivery
  • Finishing an interrupted development run

Example prompts

  • “Use the autonomous-dev skill to drive a brief, specification, issue or existing PR through implementation, review, tests and QA to a ready PR”
  • “/autonomous-dev”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep

Workflow steps

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

  1. Discover and claim. Resolve the source and search for an existing branch,
  2. Plan. Map each acceptance criterion to an implementation slice and its
  3. Implement. Use the relevant development agent, /fix or /tdd. Assign
  4. Validate and review. Run the project's configured checks. Use an
  5. QA. For user-facing changes, invoke /prepare-test-env, exercise the
  6. Publish or reuse the PR. Use /pr and the
  7. Complete. Record current validation, review, QA and CI evidence and close

What it can do on your machine

Read from SKILL.md and the folder at commit d64db2b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash
    • Glob
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files 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

Autonomous Dev loads about 2.6k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 1,262 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~71
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash, Glob, Grep

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 softspark/ai-toolkit at commit d64db2b, republished under its Apache-2.0 licence (© softspark). 1,262 words, ~2,576 tokens.

Download SKILL.mdSave it as .claude/skills/autonomous-dev/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
autonomous-dev
description
Drives a brief, specification, issue or existing PR through implementation, review, tests and QA to a ready PR. Persists ownership, progress and commit-bound evidence for safe resumption. Use for autonomous software delivery or finishing an interrupted development run.
allowed-tools
Read, Write, Edit, Bash, Glob, Grep
effort
high
argument-hint
[setup | run <task> | list | resume <run-id> | status <run-id>]

Autonomous Development

$ARGUMENTS

<!-- CLAUDE_CODE_ONLY_START -->

Only in Claude Code, apply the model-routing-patterns skill when choosing executors or creating agent definitions. Delegate to codex:codex-rescue only when its plugin is installed, enabled and callable in this session. Otherwise use the installed native agents and their configured models. A context without the Agent tool returns the dispatch decision to its supervisor; it does not invent a tool or bypass the client. Preserve explicit user choices and verify actual completion before accepting a delegated result.

<!-- CLAUDE_CODE_ONLY_END -->

Own one software-delivery run from its requested outcome to a reviewed, verified PR. Continue through reversible decisions within the user's approved scope, recording assumptions where they can be reviewed. Use existing skills for their actual work; this skill owns sequencing, state and the exit gate.

Entry points

InputAction
setupInspect the project and create its validation/tracker/QA configuration
run <brief, spec path, Jira key, issue URL or PR URL>Resolve the task, reuse existing work, then run the process
listList this repository's existing runs without changing state
resume <run-id>Read durable state, claim ownership and continue at the first unmet gate
status <run-id>Read state and report the next action; change nothing

A plain task description means run. /workflow autonomous-development routes here. A request only to review code stays with /review; an incident stays with the incident-response workflow.

Setup and authorization

Read project configuration on first use or when project commands change. Check the target repository's instructions, KB, actual build/test commands and provider identities. Keep issueTracker, codeHost and knowledge separate. For Jira/RAG projects, read the stack integration contract before discovery and reuse it for resume, QA and finalization.

Validate the reviewed configuration locally before initializing the run:

bash
python3 ${CLAUDE_SKILL_DIR}/scripts/delivery-config.py --config /absolute/project/.ai-toolkit/autonomous.json
python3 ${CLAUDE_SKILL_DIR}/scripts/delivery-config.py --config /absolute/project/.ai-toolkit/autonomous.json --task PROJ-123

Pass --task only for a Jira key/browse URL; briefs, specs and code-host PRs use their own source resolution. For Jira, use the returned canonical subject after checking the real task/instance and Git repository mapping. Preflight does not contact MCP or prove those live conditions. Configuration records project facts; it cannot grant publishing permissions, change models or relax host safeguards.

Capture the task, acceptance criteria, exclusions and authorized endpoint before implementation. The default endpoint is ready-pr. An explicit request to run this process may cover the whole plan; preserve approvals already given instead of asking at every phase. Ask only for an unresolved decision required by the task or a missing permission required by the current host. Progress independent work while the question is pending. Merge and deploy require their own explicit authorization and are not performed by the state helper.

Durable state

Use the bundled helper from the installed skill directory:

bash
python3 ${CLAUDE_SKILL_DIR}/scripts/run-state.py --help
python3 ${CLAUDE_SKILL_DIR}/scripts/run-state.py --repo /absolute/project list
python3 ${CLAUDE_SKILL_DIR}/scripts/run-state.py --repo /absolute/project init --subject brief:csv-export --objective "Export filtered orders as CSV" --source-kind brief --source "User task" --target-branch develop
python3 ${CLAUDE_SKILL_DIR}/scripts/run-state.py --repo /absolute/project status --run RUN_ID

Use actual values returned by the helper for RUN_ID, owner and artifact directory. Read state operations before the first mutation or a resume. Every writer supplies its per-session owner token. A GitHub account name is not a unique run owner. Do not initialize a replacement run to evade an existing claim, failure counter or missing evidence.

Generated state and reports live outside the target repository under its ai-toolkit session store. Store intentional specifications and regression tests in the target project's normal locations. Keep terminal output, run reports and screenshots in the helper's artifact directory so they cannot dirty the code being verified. The journal records evidence; it does not run tests or certify the truth of a report. Inspect the actual tool results before recording them.

Delivery process

Read execution and recovery for the detailed stage contract. The essential chain is:

  1. Discover and claim. Resolve the source and search for an existing branch, run and PR. For a bug, verify the symptom still exists before changing code. For Jira, refresh the scoped task; for RAG, retrieve project SOPs and rules. Freeze the relevant task/KB context in the hashed plan. Reuse the PR and its branch when present. Use an isolated worktree for new work, preserving the user's checkout.
  2. Plan. Map each acceptance criterion to an implementation slice and its verification. Record scope, ownership and dependencies. A small change needs a short plan; a specification needs explicit slices and checkpoints.
  3. Implement. Use the relevant development agent, /fix or /tdd. Assign independent work to available subagents with non-overlapping file ownership; use the current host's model and permission settings. Update affected tests and docs. Commit the coherent source change before final evidence collection.
  4. Validate and review. Run the project's configured checks. Use an independent reviewer where available, covering spec compliance and code quality. Carry inherited PR feedback forward. Fix actionable failures and re-run affected gates within the persisted attempt budget.
  5. QA. For user-facing changes, invoke /prepare-test-env, exercise the actual acceptance scenarios and capture browser/test evidence. For a change that does not need browser QA, record why and which non-UI tests cover it.
  6. Publish or reuse the PR. Use /pr and the tracker contract. Refresh the same PR after fixes. Read required checks for its current head, resolve blocking review feedback and wait only within the configured CI budget.
  7. Complete. Record current validation, review, QA and CI evidence and close the successful attempt. Require zero status blockers and satisfied tracker gates, promote/reverify an existing draft if needed, then run complete. Keep the run resumable until those external operations succeed. Report the PR, tested commit and evidence. If a gate is blocked, retain the state and report its exact resume command and remaining work.
Show full SKILL.md (378 more words)Show less

Recovery and limits

  • Resume from actual Git, tracker and journal state, not the last assistant message. Changed code makes earlier evidence stale, even when a label says approved. Refresh task requirements and relevant KB/config as well; changed acceptance criteria require a revised plan even at the same Git SHA. Required CI must refer to the same commit as the PR head.
  • Maximum five implementation/recovery attempts, a halt after three consecutive failed attempts and at least one minute between attempt starts. The journal persists these limits across sessions. Follow any stricter project limits; never reset the run to obtain another budget.
  • A stopped host has no background continuation guarantee. Leave a durable checkpoint before yielding and resume explicitly in the next invocation.
  • Release a claim on a deliberate handoff. Preserve state, reports and worktrees needed for recovery. Do not steal another session's claim or delete its work.

Completion and reporting

Completion requires a clean source checkout, the same verified commit, passing validation and review, applicable QA, satisfied required CI, and the existing PR identity. An explicit not-applicable report is allowed only for a gate declared optional during setup and with a concrete reason. An unavailable browser, failed test, pending check or missing permission is a blocker, not an exemption.

ready-pr does not set Jira Done. Finish any separately authorized, required Jira updates before immutable completion, using real transitions and reconciled receipts. Report KB indexing separately from writing the documentation.

Keep the final report short: outcome, PR, commit, verification and remaining blocker if any. End with stable chaining lines using actual values:

text
Run: <run-id>
Status: ready-pr | blocked
PR: <full URL, when created>
Commit: <verified SHA>
Resume: /autonomous-dev resume <run-id>

Gotchas

  • Committing after recording checks changes the commit identity. Collect final evidence after the code commit, and keep reports outside the checkout.
  • Tracker labels are coordination signals, not an atomic lock or proof of QA.
  • A reviewer using the same bot account may be unable to submit a formal GitHub approval. Attach the review evidence and preserve required human review gates.
  • A healthy HTTP endpoint alone does not identify the code it serves. Follow /prepare-test-env provenance rules before reusing an application instance.

/plan, /write-a-prd, /prd-to-plan, /debug, /fix, /tdd, /subagent-development, /review, /test, /lint, /build, /prepare-test-env, /pr. Invoke only the ones needed for the current stage; preserve the run's scope, ownership, approval history and budget across every handoff.

© softspark, 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

SKILL.md and 7 other files (scripts) in app/skills/autonomous-dev of softspark/ai-toolkit.

  • SKILL.md
  • reference/process.md
  • reference/project-config.md
  • reference/run-state.md
  • reference/stack-integrations.md
  • reference/tracker.md
  • scripts/delivery-config.py
  • scripts/run-state.py

Open the folder on GitHubat commit d64db2b

Compare with similar skills

Autonomous Dev 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.

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Autonomous Dev this skillsoftspark/ai-toolkit179—~2.6kAutomated safety check: NotesApache-2.0
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Agent Specificationruvnet/ruflo74k3 repos~1.8kAutomated safety check: PassMIT
Briefdavepoon/buildwithclaude3.6k—~1.3kAutomated safety check: NotesMIT
Specificity Managementthedaviddias/Front-End-Checklist74k—~477Automated safety check: PassMIT
Create Specificationgithub/awesome-copilot40k2 repos~1.4kAutomated safety check: PassMIT

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Questions about Autonomous Dev

What does Autonomous Dev do?

Drives a brief, specification, issue or existing PR through implementation, review, tests and QA to a ready PR. Autonomous Dev is an agent skill from softspark/ai-toolkit. Drives a brief, specification, issue or existing PR through implementation, review, tests and QA to a ready PR.

When should I use Autonomous Dev?

Autonomous Dev fits situations like: autonomous software delivery; finishing an interrupted development run.

How do I install Autonomous Dev in Claude Code?

Run `npx skills add softspark/ai-toolkit --skill autonomous-dev -a claude-code`. Or copy the skill folder (app/skills/autonomous-dev in softspark/ai-toolkit) into .claude/skills/autonomous-dev in your project. Claude Code loads it when a task matches its description.

How do I install Autonomous Dev in Codex?

Run `npx skills add softspark/ai-toolkit --skill autonomous-dev -a codex`. Or copy the skill folder (app/skills/autonomous-dev in softspark/ai-toolkit) into .agents/skills/autonomous-dev in your project. Codex loads it when a task matches its description.

Can I use Autonomous Dev 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 softspark/ai-toolkit --skill autonomous-dev -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/autonomous-dev, .gemini/skills/autonomous-dev, .github/skills/autonomous-dev and .opencode/skills/autonomous-dev in your project.

What does Autonomous Dev need to run?

Going by SKILL.md and its folder, Autonomous Dev needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep.

Does Autonomous Dev 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 Autonomous Dev safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. 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 Autonomous Dev use?

Autonomous Dev 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 Autonomous Dev use?

About 2.6k tokens (SKILL.md is roughly 10k 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 Autonomous Dev?

Skills that share tags, products or a category with Autonomous Dev: Brief (alirezarezvani/claude-skills, 28k stars), Agent Specification (ruvnet/ruflo, 74k stars), Brief (davepoon/buildwithclaude, 3.6k stars) and Specificity Management (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Autonomous Dev?

softspark (a GitHub user) maintains it in softspark/ai-toolkit, which has 179 GitHub stars. The repository holds 112 skills in this directory. The repository was last updated on October 7, 2026.

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