Agent skill

Autospec Tasks

by ariel-frischer in ariel-frischer/autospec

Generate YAML task breakdown from implementation plan. An agent skill from ariel-frischer/autospec.

MITAuto-check passedAgent Workflows

Install Autospec Tasks

skills CLI
$ npx skills add ariel-frischer/autospec --skill autospec-tasks -a claude-code

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

GitHub CLI
$ gh skill install ariel-frischer/autospec autospec-tasks --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/ariel-frischer/autospec.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/autospec-tasks .claude/skills/autospec-tasks && 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
autospec-tasks
GitHub stars
144
Token cost
~2.5k tokens
SKILL.md length
684 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Generate YAML task breakdown from implementation plan. An agent skill from ariel-frischer/autospec.

  • Works in 6 steps: Load design documents: Read from the… → Execute task generation workflow → Generate tasks.yaml: Create the YAML… → …
  • Tasks that involve Planning
  • SKILL.md covers User Input, Pre-computed Context, Outline and Task Generation Rules
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Autospec Tasks is an agent skill from ariel-frischer/autospec. Generate YAML task breakdown from implementation plan.

Its SKILL.md is about 2.5k 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 Agent Workflows, covering Planning, Task breakdown and User stories. The repository describes itself as: CLI for streamlined spec-driven development. The licence is MIT.

When your agent uses it

  • Tasks that involve Planning
  • Tasks that involve Task breakdown
  • Tasks that involve User stories

Example prompts

  • “/autospec-tasks”

Workflow steps

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

  1. Load design documents: Read from the feature directory
  2. Execute task generation workflow
  3. Generate tasks.yaml: Create the YAML task file with this structure
  4. Write the tasks to {{.FeatureDir}}/tasks.yaml
  5. Validate the artifact
  6. Report: Output

What it can do on your machine

Read from SKILL.md and the folder at commit 3381f26. 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 (its code samples are yaml and bash).

    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

Autospec Tasks loads about 2.5k tokens when it runs. Until then it costs about 17 tokens; SKILL.md has 684 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~17
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k

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 ariel-frischer/autospec at commit 3381f26, republished under its MIT licence (© ariel-frischer). 684 words, ~2,483 tokens.

Download SKILL.mdSave it as .claude/skills/autospec-tasks/SKILL.md (or your agent's skills folder).
name
autospec-tasks
description
Generate YAML task breakdown from implementation plan.

autospec-tasks

This Agent Skill is generated from autospec.tasks. When the user invokes "$autospec-tasks" or "/autospec.tasks", load and follow these instructions directly. Treat the text after the skill or command name as "$ARGUMENTS". Do not route back through "autospec tasks"; this skill is the prompt for the stage.

Project specs directory: ./specs

User Input

text
$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Pre-computed Context

The following paths have been pre-computed and are available for use:

  • FEATURE_DIR: {{.FeatureDir}}
  • FEATURE_SPEC: {{.FeatureSpec}}
  • IMPL_PLAN: {{.ImplPlan}}
  • AUTOSPEC_VERSION: {{.AutospecVersion}}
  • CREATED_DATE: {{.CreatedDate}}

Outline

  1. Load design documents: Read from the feature directory:

    • Required: {{.ImplPlan}} (plan.yaml) containing:
      • technical_context: tech stack, libraries, constraints
      • data_model: entities and relationships
      • api_contracts: API endpoints and schemas
      • research_findings: technical decisions
      • project_structure: file organization
    • Required: {{.FeatureSpec}} (spec.yaml) containing:
      • user_stories: with priorities (P1, P2, P3)
      • requirements: functional and non-functional
      • key_entities: initial entity identification
  2. Execute task generation workflow:

    • Extract tech stack, libraries, project structure from plan.yaml technical_context
    • Extract user stories with their priorities from spec.yaml user_stories
    • Extract entities from plan.yaml data_model and map to user stories
    • Map endpoints from plan.yaml api_contracts to user stories
    • Extract decisions from plan.yaml research_findings for setup tasks
    • Generate tasks organized by user story (see Task Generation Rules below)
    • Define the user story completion order
    • Identify phase ordering and task dependencies
    • Validate task completeness (each user story has all needed tasks)
  3. Generate tasks.yaml: Create the YAML task file with this structure:

    yaml
    tasks:
      branch: "<current git branch>"
      created: "<today's date YYYY-MM-DD>"
      spec_path: "<relative path to spec file>"
      plan_path: "<relative path to plan file>"
    
    summary:
      total_tasks: <number>
      total_phases: <number>
      parallel_opportunities: <number of tasks marked parallelizable>
      estimated_complexity: "<low|medium|high>"
    
    phases:
      - number: 1
        title: "Setup"
        purpose: "Project initialization and new package structure"
        tasks:
          - id: "T001"
            title: "<task title with file path>"
            status: "Pending"  # Pending | InProgress | Completed
            type: "setup"  # setup | implementation | test | documentation | refactor
            parallel: false
            story_id: null  # null for setup/foundational tasks
            file_path: "<exact file path to create/modify>"
            dependencies: []
            acceptance_criteria:
              - "<criterion 1>"
    
      - number: 2
        title: "Foundational"
        purpose: "Core infrastructure that MUST be complete before user stories"
        tasks:
          - id: "T002"
            title: "<task title>"
            status: "Pending"
            type: "implementation"
            parallel: true  # Can run in parallel with T003
            story_id: null
            file_path: "<file path>"
            dependencies: ["T001"]
            acceptance_criteria:
              - "<criterion>"
    
      - number: 3
        title: "User Story 1 - <US-001 title from spec>"
        purpose: "<goal from user story>"
        story_reference: "US-001"
        independent_test: "<how to test this story independently>"
        tasks:
          - id: "T010"
            title: "<task with file path>"
            status: "Pending"
            type: "test"  # Tests first per constitution
            parallel: true
            story_id: "US-001"
            file_path: "<test file path>"
            dependencies: ["T002"]
            acceptance_criteria:
              - "<criterion>"
    
          - id: "T011"
            title: "<implementation task>"
            status: "Pending"
            type: "implementation"
            parallel: false
            story_id: "US-001"
            file_path: "<source file path>"
            dependencies: ["T010"]  # Depends on test being written
            acceptance_criteria:
              - "<criterion>"
    
      # Continue with more phases for each user story...
    
      - number: <final>
        title: "Polish & Cross-Cutting Concerns"
        purpose: "Improvements that affect multiple user stories"
        tasks:
          - id: "T099"
            title: "<polish task>"
            status: "Pending"
            type: "refactor"
            parallel: true
            story_id: null
            file_path: "<file path>"
            dependencies: ["<all prior phases>"]
            acceptance_criteria:
              - "<criterion>"
    
    dependencies:
      user_story_order:
        - story_id: "US-001"
          depends_on: []
          blocks: ["US-002"]
        - story_id: "US-002"
          depends_on: ["US-001"]
          blocks: []
    
      phase_order:
        - phase: 1
          blocks: [2]
        - phase: 2
          blocks: [3, 4, 5]
    
    parallel_execution:
      - phase: 2
        parallel_groups:
          - tasks: ["T002", "T003"]
            rationale: "Different packages, no dependencies"
      - phase: 3
        parallel_groups:
          - tasks: ["T010", "T011"]
            rationale: "Test and implementation can be developed together"
    
    implementation_strategy:
      mvp_scope:
        phases: [1, 2, 3]
        description: "Setup + Foundational + User Story 1"
        validation: "<how to validate MVP>"
      incremental_delivery:
        - milestone: "Foundation Ready"
          phases: [1, 2]
          deliverable: "<what's usable at this point>"
        - milestone: "MVP Complete"
          phases: [1, 2, 3]
          deliverable: "<what's usable>"
    
    _meta:
      version: "1.0.0"
      generator: "autospec"
      generator_version: "{{.AutospecVersion}}"
      created: "{{.CreatedDate}}"
      artifact_type: "tasks"
  4. Write the tasks to {{.FeatureDir}}/tasks.yaml

  5. Validate the artifact:

    bash
    autospec artifact {{.FeatureDir}}/tasks.yaml
    • If validation fails: fix schema errors (missing required fields, invalid types, invalid dependencies) and retry
    • If validation passes: proceed to report
  6. Report: Output:

    • Full path to tasks.yaml
    • Total task count
    • Task count per phase
    • Task count per user story
    • Parallel opportunities identified
    • Suggested MVP scope
    • Format validation confirmation

Context for task generation: $ARGUMENTS

The tasks.yaml should be immediately executable - each task must be specific enough that an LLM can complete it without additional context.

Show full SKILL.md (367 more words)Show less

Task Generation Rules

CRITICAL: Tasks MUST be organized by user story to enable independent implementation and testing.

Tests are REQUIRED for new behavior whenever practical: Generate test tasks before implementation tasks when the feature changes behavior. Tests may be omitted only for documentation-only changes, configuration-only changes with no behavior change, or explicitly marked spike/prototype work.

Final tasks: Include project-appropriate polish, documentation, validation, or release-note tasks when required by the specification, implementation plan, or project governance.

Task ID Format

Every task MUST have:

  1. Task ID: Sequential format T001, T002, T003... in execution order
  2. Parallel flag: parallel: true if task can run alongside others (different files, no dependencies)
  3. Story ID: Link to user story (US-001, US-002) for story-phase tasks, null for setup/foundational
  4. File path: Exact path where work happens
  5. Dependencies: List of task IDs that must complete first
Task Organization
  1. From User Stories (spec) - PRIMARY ORGANIZATION:

    • Each user story (P1, P2, P3...) gets its own phase
    • Map all related components to their story:
      • Models needed for that story
      • Services needed for that story
      • Endpoints/UI needed for that story
      • Tests specific to that story (if requested)
    • Mark story dependencies (most stories should be independent)
  2. From Plan Structure:

    • Map each component from project_structure to appropriate phase
    • If tests requested: Each component → test task before implementation
  3. From Data Model:

    • Map each entity to the user story(ies) that need it
    • If entity serves multiple stories: Put in earliest story or Foundational phase
    • Relationships → service layer tasks in appropriate story phase
  4. From Setup/Infrastructure:

    • Shared infrastructure → Setup phase (Phase 1)
    • Foundational/blocking tasks → Foundational phase (Phase 2)
    • Story-specific setup → within that story's phase
Phase Structure
  • Phase 1: Setup (project initialization)
  • Phase 2: Foundational (blocking prerequisites - MUST complete before user stories)
  • Phase 3+: User Stories in priority order (P1, P2, P3...)
    • Within each story: Tests (if requested) → Models → Services → Endpoints → Integration
    • Each phase should be a complete, independently testable increment
  • Final Phase: Polish & Cross-Cutting Concerns
Task Types
  • setup: Project/directory initialization
  • test: Test file creation (should come before implementation if TDD)
  • implementation: Core feature code
  • documentation: README, docs, comments
  • refactor: Code improvement without behavior change
Task Status
  • Pending: Not started
  • InProgress: Currently being worked on
  • Completed: Finished and verified

© ariel-frischer, 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/autospec-tasks of ariel-frischer/autospec.

Open the folder on GitHubat commit 3381f26

Compare with similar skills

Autospec Tasks 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.

Autospec Tasks compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Autospec Tasks this skillariel-frischer/autospec144—~2.5kAutomated safety check: PassMIT
Plannerpenpot/penpot61k—~2.7kAutomated safety check: PassMPL-2.0
Speckit Tasksforyourhealth111-pixel/Vibe-Skills3.6k—~1.6kAutomated safety check: PassApache-2.0
Planning And Task Breakdownskuramatata/my-pi-agent114—~679Automated safety check: PassNone
Wayfinder Planning Mapsrengwu/wayfinder-maps137—~3.5kAutomated safety check: PassMIT
Gen Planalibaba/atrex-kernel-agent168—~3.4kAutomated safety check: PassMIT

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Questions about Autospec Tasks

What does Autospec Tasks do?

Generate YAML task breakdown from implementation plan. An agent skill from ariel-frischer/autospec. Autospec Tasks is an agent skill from ariel-frischer/autospec. Generate YAML task breakdown from implementation plan.

When should I use Autospec Tasks?

Autospec Tasks fits situations like: tasks that involve Planning; tasks that involve Task breakdown; tasks that involve User stories.

How do I install Autospec Tasks in Claude Code?

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

How do I install Autospec Tasks in Codex?

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

Can I use Autospec Tasks 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 ariel-frischer/autospec --skill autospec-tasks -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/autospec-tasks, .gemini/skills/autospec-tasks, .github/skills/autospec-tasks and .opencode/skills/autospec-tasks in your project.

What does Autospec Tasks need to run?

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

Does Autospec Tasks 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 Autospec Tasks 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 Autospec Tasks use?

Autospec Tasks 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 Autospec Tasks use?

About 2.5k tokens (SKILL.md is roughly 9.9k 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 Autospec Tasks?

Skills that share tags, products or a category with Autospec Tasks: Planner (penpot/penpot, 61k stars), Speckit Tasks (foryourhealth111-pixel/Vibe-Skills, 3.6k stars), Planning And Task Breakdown (skuramatata/my-pi-agent, 114 stars) and Wayfinder Planning Maps (rengwu/wayfinder-maps, 137 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Autospec Tasks?

ariel-frischer (a GitHub user) maintains it in ariel-frischer/autospec, which has 144 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 28, 2026.

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