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Agent skill

Dev Lifecycle

by codeaholicguy in codeaholicguy/ai-devkit

AI DevKit · Orchestrator for structured SDLC phase skills. An agent skill from codeaholicguy/ai-devkit.

Apache-2.0Auto-check passedAgent Workflows

Install Dev Lifecycle

skills CLI
$ npx skills add codeaholicguy/ai-devkit --skill dev-lifecycle -a claude-code

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

GitHub CLI
$ gh skill install codeaholicguy/ai-devkit dev-lifecycle --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/codeaholicguy/ai-devkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dev-lifecycle .claude/skills/dev-lifecycle && 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
dev-lifecycle
GitHub stars
1.6k
Token cost
~1.7k tokens
SKILL.md length
898 words
Files
3 (incl. scripts)
Skills in repo
28
Repo updated
First seen
Licence
Apache-2.0

At a glance

AI DevKit · Orchestrator for structured SDLC phase skills. An agent skill from codeaholicguy/ai-devkit.

  • Works in 9 steps: Run npx ai-devkit@latest skill list to… → Confirm the listed skills include all… → If any required skill is missing, run… → …
  • The user wants to run the full lifecycle
  • SKILL.md covers Startup Validation, Plan Before Execution, Phase Routing and Resuming Work, plus 2 more sections
  • Runs Shell scripts from its folder; calls npx

What it does

Dev Lifecycle is an agent skill from codeaholicguy/ai-devkit. AI DevKit · Orchestrator for structured SDLC phase skills. Use when the user wants to run the full lifecycle or choose the next phase across requirements, design, planning, implementation, testing, and review.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `agents/openai.yaml` and `scripts/check-status.sh`).

It sits in Agent Workflows. The repository describes itself as: The control plane for AI coding agents. The licence is Apache-2.0.

When your agent uses it

  • The user wants to run the full lifecycle
  • Choose the next phase across requirements

Example prompts

  • “/dev-lifecycle”

Requirements

  • Node.js
  • A Bash shell

Workflow steps

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

  1. Run npx ai-devkit@latest skill list to inspect currently installed project skills.
  2. Confirm the listed skills include all required phase skills and supporting skills.
  3. If any required skill is missing, run npx ai-devkit@latest skill add --built-in to install all AI DevKit built-in skills. Then rerun npx…
  4. If installation fails or a required skill is still missing, stop and report the missing skill names and command output summary. Do not run…
  5. Run npx ai-devkit@latest lint to verify the configured AI docs structure.
  6. If working on a specific feature, run npx ai-devkit@latest lint --feature .
  7. If lint fails because project docs are not initialized, run npx ai-devkit@latest init -a -e claude --built-in --yes, then rerun lint.
  8. Probe optional task tracing availability
  9. When working on a specific feature and task tracing is available

What it can do on your machine

Read from SKILL.md and the folder at commit 7ef0cd5. 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

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • 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

Dev Lifecycle loads about 1.7k tokens when it runs. Until then it costs about 56 tokens; SKILL.md has 898 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~56
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from codeaholicguy/ai-devkit at commit 7ef0cd5, republished under its Apache-2.0 licence (© codeaholicguy). 898 words, ~1,708 tokens.

Download SKILL.mdSave it as .claude/skills/dev-lifecycle/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
dev-lifecycle
description
AI DevKit · Orchestrator for structured SDLC phase skills. Use when the user wants to run the full lifecycle or choose the next phase across requirements, design, planning, implementation, testing, and review.

Dev Lifecycle

Coordinate the phase-specific AI DevKit skills instead of running phase details directly.

Required phase skills:

  • dev-worktree for feature workspace setup and resume.
  • dev-requirements for phases 1-2: new requirement and requirements review.
  • dev-design for phase 3: design review.
  • dev-planning for phases 4 and 6: initial task planning and updates after implementation tasks.
  • dev-implementation for phases 5 and 7: execute plan and check implementation.
  • dev-testing for phase 8: write tests and verify coverage.
  • dev-review for phase 9: final code review.

Supporting skills:

  • memory for reusable project knowledge during clarification.
  • tdd for implementation tasks.
  • verify before completing implementation, implementation checks, testing claims, and review readiness.
  • task for optional progress tracing when the task command is usable.

Startup Validation

At the beginning of every dev-lifecycle run:

  1. Run npx ai-devkit@latest skill list to inspect currently installed project skills.
  2. Confirm the listed skills include all required phase skills and supporting skills.
  3. If any required skill is missing, run npx ai-devkit@latest skill add --built-in to install all AI DevKit built-in skills. Then rerun npx ai-devkit@latest skill list.
  4. If installation fails or a required skill is still missing, stop and report the missing skill names and command output summary. Do not run a phase without its skill.
  5. Run npx ai-devkit@latest lint to verify the configured AI docs structure.
  6. If working on a specific feature, run npx ai-devkit@latest lint --feature <name>.
  7. If lint fails because project docs are not initialized, run npx ai-devkit@latest init -a -e claude --built-in --yes, then rerun lint.
  8. Probe optional task tracing availability:
    • With a feature: npx ai-devkit@latest task list --name <feature-name> --json
    • Without a feature: npx ai-devkit@latest task list --json
    • Treat task tracing as available only if the read probe exits 0. If it fails, record task tracing as unavailable with the failed command and reason, then continue without task logging.
    • Never block lifecycle work only because the task command is missing or unusable.
  9. When working on a specific feature and task tracing is available:
    • Load and follow task before executing a phase.
    • Initialize or show the task named after the feature, mark active work, and emit phase/progress/next/blocker/evidence events per task.
    • Sequence task mutations; do not batch or parallelize mutations for the same feature.

Plan Before Execution

Before executing any phase:

  1. Identify the target feature, current docs state, branch/worktree context, and likely next phase.
  2. Propose a concise plan that names the phase skill to use, the docs/files to read, commands to run, expected edits, task tracing status and planned task events if tracing is available, and verification evidence.
  3. Wait for user approval before executing the plan unless the user already gave explicit approval for that exact phase execution.
  4. After approval, load and follow only the selected phase skill plus any explicitly required supporting skills. If tracing is available, the task skill is explicitly required.

Phase Routing

PhaseRoute toWhen
Setup. Workspacedev-worktreeStarting or resuming feature work
1. New Requirementdev-requirementsUser wants to add a feature or start /new-requirement
2. Review Requirementsdev-requirementsRequirements doc needs validation
3. Review Designdev-designDesign doc needs validation against requirements
4. Create Initial Plandev-planningRequirements, design, and testing docs are ready for task breakdown
5. Execute Plandev-implementationReady to implement tasks from planning doc
6. Update Planningdev-planningAuto-trigger after completing any implementation task
7. Check Implementationdev-implementationVerify code matches design and docs
8. Write Testsdev-testingAdd or verify test coverage
9. Code Reviewdev-reviewFinal pre-push review

Sequential flow: setup -> 1 -> 2 -> 3 -> 4 -> 5 -> 6 after each completed task -> 7 -> 8 -> 9.

Show full SKILL.md (300 more words)Show less

Resuming Work

If the user wants to continue work on an existing feature:

  1. Use dev-worktree to identify and confirm the target branch/worktree.
  2. Run npx ai-devkit@latest lint --feature <feature-name> in the active context.
  3. Run the phase detector from the installed dev-lifecycle skill directory:
    • Resolve <skill-dir> as the directory containing this SKILL.md.
    • Run <skill-dir>/scripts/check-status.sh <feature-name>.
    • Use the suggested phase when proposing the execution plan.

Backward Transitions

Not every phase moves forward. When a phase reveals problems, route back:

  • Requirements review finds fundamental gaps: return to dev-requirements Phase 1.
  • Design review finds requirements gaps: return to dev-requirements Phase 2.
  • Design review finds design flaws: stay in dev-design and revise design.
  • Implementation check finds major deviations: return to dev-design if design is wrong, or dev-implementation if code is wrong.
  • Testing reveals design flaws: return to dev-design.
  • Review finds blocking issues: return to dev-implementation or dev-testing.

Rules

  • Use npx ai-devkit@latest lint and npx ai-devkit@latest lint --feature <name> to discover and validate the configured docs directory. Do not assume docs/ai; it is only the default.
  • Read existing configured AI docs before changes. Keep diffs minimal.
  • Keep feature names aligned with branch/worktree feature-<name>.
  • New feature docs come from npx ai-devkit@latest docs init-feature <name>. Use the paths returned by the command as authoritative.
  • Existing feature docs are the paths reported or validated by npx ai-devkit@latest lint --feature <name>. If you must infer manually, first resolve the configured docs directory from .ai-devkit.json paths.docs, falling back to docs/ai.
  • After each phase, summarize output and suggest the next phase.
  • Do not claim completion without fresh verification evidence.
  • When task tracing is available, follow task: create once, assign actor when known, mark active/blocked, set phase, record progress/next/evidence, and close only after final verification/review. If tracing is unavailable, include failed probe commands in the phase summary without blocking the lifecycle.

© codeaholicguy, 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 2 other files (scripts) in skills/dev-lifecycle of codeaholicguy/ai-devkit.

  • SKILL.md
  • agents/openai.yaml
  • scripts/check-status.sh

Open the folder on GitHubat commit 7ef0cd5

Compare with similar skills

Dev Lifecycle 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.

Dev Lifecycle compared with similar skills
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Dev Lifecycle this skillcodeaholicguy/ai-devkit1.6k—~1.7kAutomated safety check: PassApache-2.0
MCP Server Builderanthropics/skills180k64 repos~2.3kAutomated safety check: PassApache-2.0
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k11 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers296k2 repos~5.1kAutomated safety check: PassMIT
Claude Code Agent Developmentanthropics/claude-plugins-official38k8 repos~2.8kAutomated safety check: PassApache-2.0

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Categories

Questions about Dev Lifecycle

What does Dev Lifecycle do?

AI DevKit · Orchestrator for structured SDLC phase skills. An agent skill from codeaholicguy/ai-devkit. Dev Lifecycle is an agent skill from codeaholicguy/ai-devkit. AI DevKit · Orchestrator for structured SDLC phase skills.

When should I use Dev Lifecycle?

Dev Lifecycle fits situations like: the user wants to run the full lifecycle; choose the next phase across requirements.

How do I install Dev Lifecycle in Claude Code?

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

How do I install Dev Lifecycle in Codex?

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

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

What does Dev Lifecycle need to run?

Going by SKILL.md and its folder, Dev Lifecycle needs a shell for the scripts in its folder and the command-line tools its instructions call (npx). Our summary lists: Node.js; A Bash shell.

Does Dev Lifecycle 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 Dev Lifecycle 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Dev Lifecycle use?

Dev Lifecycle 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 Dev Lifecycle use?

About 1.7k tokens (SKILL.md is roughly 6.8k 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 Dev Lifecycle?

Skills that share tags, products or a category with Dev Lifecycle: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 296k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dev Lifecycle?

codeaholicguy (a GitHub user) maintains it in codeaholicguy/ai-devkit, which has 1,642 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 7, 2026.

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