Agent skill

Spec Generator

by catlog22 in catlog22/Claude-Code-Workflow

Specification generator - 7 phase document chain producing product brief, PRD, architecture, epics, and issues with Codex review gates.

MITAuto-check: notesProduct & Project Management

Install Spec Generator

skills CLI
$ npx skills add catlog22/Claude-Code-Workflow --skill spec-generator -a claude-code

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

GitHub CLI
$ gh skill install catlog22/Claude-Code-Workflow spec-generator --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/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/spec-generator .claude/skills/spec-generator && 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
spec-generator
GitHub stars
2.1k
Token cost
~4.3k tokens
SKILL.md length
798 words
Files
20
Skills in repo
82
Repo updated
First seen
Licence
MIT

At a glance

Specification generator - 7 phase document chain producing product brief, PRD, architecture, epics, and issues with Codex review gates.

  • Works in 8 steps: Discovery → 5: Requirement Expansion & Clarification → Product Brief → …
  • Create specification
  • SKILL.md covers Architecture Overview, Key Design Principles, Mandatory Prerequisites and Execution Flow, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Spec Generator is an agent skill from catlog22/Claude-Code-Workflow. Specification generator - 7 phase document chain producing product brief, PRD, architecture, epics, and issues with Codex review gates. Triggers on generate spec, create specification, spec generator, workflow:spec.

Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 23 other files (for example `README.md`, `phases/01-5-requirement-clarification.md` and `phases/01-discovery.md`).

It sits in Product & Project Management, covering User stories, PRD writing and Human-in-the-loop approvals. The repository describes itself as: JSON-driven multi-agent cadence-team development framework with intelligent CLI orchestration (Gemini/Qwen/Codex), context-first architecture, and automated workflow execution. The licence is MIT.

When your agent uses it

  • Create specification
  • Tasks that involve User stories
  • Tasks that involve PRD writing

Example prompts

  • “/spec-generator”

Requirements

  • Pre-approved tools (allowed-tools): Agent, AskUserQuestion, TaskCreate, TaskUpdate, TaskList, Read, Write, Edit, Bash, Glob, Grep, Skill

Workflow steps

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

  1. Discovery
  2. 5: Requirement Expansion & Clarification
  3. Product Brief
  4. Requirements
  5. Architecture
  6. Epics & Stories
  7. Readiness Check
  8. 5: Auto-Fix

What it can do on your machine

Read from SKILL.md and the folder at commit 07491b0. 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:

    • Agent
    • AskUserQuestion
    • TaskCreate
    • TaskUpdate
    • TaskList
    • Read
    • Write
    • Edit
    • Bash
    • Glob

    …and 2 more on the same allowed-tools line.

    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 javascript and json).

    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

Spec Generator loads about 4.3k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 798 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k

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: Agent, AskUserQuestion, TaskCreate, TaskUpdate, TaskList, Read, Write, Edit, Bash, Glob, Grep, Skill

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 catlog22/Claude-Code-Workflow at commit 07491b0, republished under its MIT licence (© catlog22). 798 words, ~4,343 tokens.

Download SKILL.mdSave it as .claude/skills/spec-generator/SKILL.md (or your agent's skills folder). This skill also uses 19 other files; get the full folder from GitHub.
name
spec-generator
description
Specification generator - 7 phase document chain producing product brief, PRD, architecture, epics, and issues with Codex review gates. Triggers on generate spec, create specification, spec generator, workflow:spec.
allowed-tools
Agent, AskUserQuestion, TaskCreate, TaskUpdate, TaskList, Read, Write, Edit, Bash, Glob, Grep, Skill

Spec Generator

Structured specification document generator producing a complete specification package (Product Brief, PRD, Architecture, Epics) through 6 sequential phases with multi-CLI analysis and interactive refinement. Document generation only - execution handoff to existing workflows (lite-plan, plan, req-plan).

Architecture Overview

Phase 0:   Specification Study (Read specs/ + templates/ - mandatory prerequisite)
           |
Phase 1:   Discovery               -> spec-config.json + discovery-context.json
           |                           (includes spec_type selection)
Phase 1.5: Req Expansion           -> refined-requirements.json (interactive discussion + CLI gap analysis)
           |                           (-y auto mode: auto-expansion, skip interaction)
Phase 2:   Product Brief            -> product-brief.md + glossary.json  (multi-CLI parallel analysis)
           |
Phase 3:   Requirements (PRD)      -> requirements/  (_index.md + REQ-*.md + NFR-*.md)
           |                           (RFC 2119 keywords, data model definitions)
Phase 4:   Architecture            -> architecture/  (_index.md + ADR-*.md, multi-CLI review)
           |                           (state machine, config model, error handling, observability)
Phase 5:   Epics & Stories         -> epics/  (_index.md + EPIC-*.md)
           |
Phase 6:   Readiness Check         -> readiness-report.md + spec-summary.md
           |                           (terminology + scope consistency validation)
           ├── Pass (>=80%): Handoff to execution workflows
           ├── Review (60-79%): Handoff with caveats
           └── Fail (<60%): Phase 6.5 Auto-Fix (max 2 iterations)
                 |
Phase 6.5: Auto-Fix               -> Updated Phase 2-5 documents
                 |
                 └── Re-run Phase 6 validation

Key Design Principles

  1. Document Chain: Each phase builds on previous outputs, creating a traceable specification chain from idea to executable stories
  2. Multi-Perspective Analysis: CLI tools (Gemini/Codex/Claude) provide product, technical, and user perspectives in parallel
  3. Interactive by Default: Each phase offers user confirmation points; -y flag enables full auto mode
  4. Resumable Sessions: spec-config.json tracks completed phases; -c flag resumes from last checkpoint
  5. Template-Driven: All documents generated from standardized templates with YAML frontmatter
  6. Pure Documentation: No code generation or execution - clean handoff to existing execution workflows
  7. Spec Type Specialization: Templates adapt to spec type (service/api/library/platform) via profiles for domain-specific depth
  8. Iterative Quality: Phase 6.5 auto-fix loop repairs issues found in readiness check (max 2 iterations)
  9. Terminology Consistency: glossary.json generated in Phase 2, injected into all subsequent phases

Mandatory Prerequisites

Do NOT skip: Before performing any operations, you must completely read the following documents. Proceeding without reading the specifications will result in outputs that do not meet quality standards.

Specification Documents (Required Reading)
DocumentPurposePriority
specs/document-standards.mdDocument format, frontmatter, naming conventionsP0 - Must read before execution
specs/quality-gates.mdPer-phase quality gate criteria and scoringP0 - Must read before execution
Template Files (Must read before generation)
DocumentPurpose
templates/product-brief.mdProduct brief document template
templates/requirements-prd.mdPRD document template
templates/architecture-doc.mdArchitecture document template
templates/epics-template.mdEpic/Story document template

Execution Flow

Input Parsing:
   |- Parse $ARGUMENTS: extract idea/topic, flags (-y, -c, -m)
   |- Detect mode: new | continue
   |- If continue: read spec-config.json, resume from first incomplete phase
   |- If new: proceed to Phase 1

Phase 1: Discovery & Seed Analysis
   |- Ref: phases/01-discovery.md
   |- Generate session ID: SPEC-{slug}-{YYYY-MM-DD}
   |- Parse input (text or file reference)
   |- Gemini CLI seed analysis (problem, users, domain, dimensions)
   |- Codebase exploration (conditional, if project detected)
   |- Spec type selection: service|api|library|platform (interactive, -y defaults to service)
   |- User confirmation (interactive, -y skips)
   |- Output: spec-config.json, discovery-context.json (optional)

Phase 1.5: Requirement Expansion & Clarification
   |- Ref: phases/01-5-requirement-clarification.md
   |- CLI gap analysis: completeness scoring, missing dimensions detection
   |- Multi-round interactive discussion (max 5 rounds)
   |  |- Round 1: present gap analysis + expansion suggestions
   |  |- Round N: follow-up refinement based on user responses
   |- User final confirmation of requirements
   |- Auto mode (-y): CLI auto-expansion without interaction
   |- Output: refined-requirements.json

Phase 2: Product Brief
   |- Ref: phases/02-product-brief.md
   |- 3 parallel CLI analyses: Product (Gemini) + Technical (Codex) + User (Claude)
   |- Synthesize perspectives: convergent themes + conflicts
   |- Generate glossary.json (terminology from product brief + CLI analysis)
   |- Interactive refinement (-y skips)
   |- Output: product-brief.md (from template), glossary.json

Phase 3: Requirements / PRD
   |- Ref: phases/03-requirements.md
   |- Gemini CLI: expand goals into functional + non-functional requirements
   |- Generate acceptance criteria per requirement
   |- RFC 2119 behavioral constraints (MUST/SHOULD/MAY)
   |- Core entity data model definitions
   |- Glossary injection for terminology consistency
   |- User priority sorting: MoSCoW (interactive, -y auto-assigns)
   |- Output: requirements/ directory (_index.md + REQ-*.md + NFR-*.md, from template)

Phase 4: Architecture
   |- Ref: phases/04-architecture.md
   |- Gemini CLI: core components, tech stack, ADRs
   |- Codebase integration mapping (conditional)
   |- State machine generation (ASCII diagrams for lifecycle entities)
   |- Configuration model definition (fields, types, defaults, constraints)
   |- Error handling strategy (per-component classification + recovery)
   |- Observability specification (metrics, logs, health checks)
   |- Spec type profile injection (templates/profiles/{type}-profile.md)
   |- Glossary injection for terminology consistency
   |- Codex CLI: architecture challenge + review
   |- Interactive ADR decisions (-y auto-accepts)
   |- Output: architecture/ directory (_index.md + ADR-*.md, from template)

Phase 5: Epics & Stories
   |- Ref: phases/05-epics-stories.md
   |- Gemini CLI: requirement grouping into Epics, MVP subset tagging
   |- Story generation: As a...I want...So that...
   |- Dependency mapping (Mermaid)
   |- Interactive validation (-y skips)
   |- Output: epics/ directory (_index.md + EPIC-*.md, from template)

Phase 6: Readiness Check
   |- Ref: phases/06-readiness-check.md
   |- Cross-document validation (completeness, consistency, traceability)
   |- Quality scoring per dimension
   |- Terminology consistency validation (glossary compliance)
   |- Scope containment validation (PRD <= Brief scope)
   |- Output: readiness-report.md, spec-summary.md
   |- Handoff options: lite-plan, req-plan, plan, issue:new, export only, iterate

Phase 6.5: Auto-Fix (conditional, triggered when Phase 6 score < 60%)
   |- Ref: phases/06-5-auto-fix.md
   |- Parse readiness-report.md for Error/Warning items
   |- Group issues by originating Phase (2-5)
   |- Re-generate affected sections via CLI with error context
   |- Re-run Phase 6 validation
   |- Max 2 iterations, then force handoff
   |- Output: Updated Phase 2-5 documents

Complete: Full specification package ready for execution

Phase 6 → Handoff Bridge (conditional, based on user selection):
   ├─ lite-plan: Extract first MVP Epic description → direct text input
   ├─ plan / req-plan: Create WFS session + .brainstorming/ bridge files
   │   ├─ guidance-specification.md (synthesized from spec outputs)
   │   ├─ feature-specs/feature-index.json (Epic → Feature mapping)
   │   └─ feature-specs/F-{num}-{slug}.md (one per Epic)
   ├─ issue:new: Create issues per Epic
   └─ context-search-agent auto-discovers .brainstorming/
       → context-package.json.brainstorm_artifacts populated
       → action-planning-agent consumes: guidance_spec (P1) → feature_index (P2)

Directory Setup

javascript
// Session ID generation
const slug = topic.toLowerCase().replace(/[^a-z0-9\u4e00-\u9fff]+/g, '-').slice(0, 40);
const date = new Date().toISOString().slice(0, 10);
const sessionId = `SPEC-${slug}-${date}`;
const workDir = `.workflow/.spec/${sessionId}`;

Bash(`mkdir -p "${workDir}"`);

Output Structure

.workflow/.spec/SPEC-{slug}-{YYYY-MM-DD}/
├── spec-config.json              # Session configuration + phase state
├── discovery-context.json        # Codebase exploration results (optional)
├── refined-requirements.json     # Phase 1.5: Confirmed requirements after discussion
├── glossary.json                 # Phase 2: Terminology glossary for cross-doc consistency
├── product-brief.md              # Phase 2: Product brief
├── requirements/                 # Phase 3: Detailed PRD (directory)
│   ├── _index.md                 #   Summary, MoSCoW table, traceability, links
│   ├── REQ-NNN-{slug}.md         #   Individual functional requirement
│   └── NFR-{type}-NNN-{slug}.md  #   Individual non-functional requirement
├── architecture/                 # Phase 4: Architecture decisions (directory)
│   ├── _index.md                 #   Overview, components, tech stack, links
│   └── ADR-NNN-{slug}.md         #   Individual Architecture Decision Record
├── epics/                        # Phase 5: Epic/Story breakdown (directory)
│   ├── _index.md                 #   Epic table, dependency map, MVP scope
│   └── EPIC-NNN-{slug}.md        #   Individual Epic with Stories
├── readiness-report.md           # Phase 6: Quality report
└── spec-summary.md               # Phase 6: One-page executive summary

State Management

spec-config.json serves as core state file:

json
{
  "session_id": "SPEC-xxx-2026-02-11",
  "seed_input": "User input text",
  "input_type": "text",
  "timestamp": "ISO8601",
  "mode": "interactive",
  "complexity": "moderate",
  "depth": "standard",
  "focus_areas": [],
  "spec_type": "service",
  "iteration_count": 0,
  "iteration_history": [],
  "seed_analysis": {
    "problem_statement": "...",
    "target_users": [],
    "domain": "...",
    "constraints": [],
    "dimensions": []
  },
  "has_codebase": false,
  "refined_requirements_file": "refined-requirements.json",
  "phasesCompleted": [
    { "phase": 1, "name": "discovery", "output_file": "spec-config.json", "completed_at": "ISO8601" },
    { "phase": 1.5, "name": "requirement-clarification", "output_file": "refined-requirements.json", "discussion_rounds": 2, "completed_at": "ISO8601" },
    { "phase": 3, "name": "requirements", "output_dir": "requirements/", "output_index": "requirements/_index.md", "file_count": 8, "completed_at": "ISO8601" }
  ]
}

Resume mechanism: -c|--continue flag reads spec-config.json.phasesCompleted, resumes from first incomplete phase.

Core Rules

  1. Start Immediately: First action is TaskCreate initialization, then Phase 0 (spec study), then Phase 1
  2. Progressive Phase Loading: Read phase docs ONLY when that phase is about to execute
  3. Auto-Continue: All phases run autonomously; check TaskList to execute next pending phase
  4. Parse Every Output: Extract required data from each phase for next phase context
  5. DO NOT STOP: Continuous 6-phase pipeline until all phases complete or user exits
  6. Respect -y Flag: When auto mode, skip all AskUserQuestion calls, use recommended defaults
  7. Respect -c Flag: When continue mode, load spec-config.json and resume from checkpoint
  8. Inject Glossary: From Phase 3 onward, inject glossary.json terms into every CLI prompt
  9. Load Profile: Read templates/profiles/{spec_type}-profile.md and inject requirements into Phase 2-5 prompts
  10. Iterate on Failure: When Phase 6 score < 60%, auto-trigger Phase 6.5 (max 2 iterations)

Reference Documents by Phase

Phase 1: Discovery
DocumentPurposeWhen to Use
phases/01-discovery.mdSeed analysis and session setupPhase start
templates/profiles/Spec type profilesSpec type selection
specs/document-standards.mdFrontmatter format for spec-config.jsonConfig generation
Phase 1.5: Requirement Expansion & Clarification
DocumentPurposeWhen to Use
phases/01-5-requirement-clarification.mdInteractive requirement discussion workflowPhase start
specs/quality-gates.mdQuality criteria for refined requirementsValidation
Show full SKILL.md (314 more words)Show less
Phase 2: Product Brief
DocumentPurposeWhen to Use
phases/02-product-brief.mdMulti-CLI analysis orchestrationPhase start
templates/product-brief.mdDocument templateDocument generation
specs/glossary-template.jsonGlossary schemaGlossary generation
Phase 3: Requirements
DocumentPurposeWhen to Use
phases/03-requirements.mdPRD generation workflowPhase start
templates/requirements-prd.mdDocument templateDocument generation
Phase 4: Architecture
DocumentPurposeWhen to Use
phases/04-architecture.mdArchitecture decision workflowPhase start
templates/architecture-doc.mdDocument templateDocument generation
Phase 5: Epics & Stories
DocumentPurposeWhen to Use
phases/05-epics-stories.mdEpic/Story decompositionPhase start
templates/epics-template.mdDocument templateDocument generation
Phase 6: Readiness Check
DocumentPurposeWhen to Use
phases/06-readiness-check.mdCross-document validationPhase start
specs/quality-gates.mdQuality scoring criteriaValidation
Phase 6.5: Auto-Fix
DocumentPurposeWhen to Use
phases/06-5-auto-fix.mdAuto-fix workflow for readiness issuesWhen Phase 6 score < 60%
specs/quality-gates.mdIteration exit criteriaValidation
Debugging & Troubleshooting
IssueSolution Document
Phase execution failedRefer to the relevant Phase documentation
Output does not meet expectationsspecs/quality-gates.md
Document format issuesspecs/document-standards.md

Error Handling

PhaseErrorBlocking?Action
Phase 1Empty inputYesError and exit
Phase 1CLI seed analysis failsNoUse basic parsing fallback
Phase 1.5Gap analysis CLI failsNoSkip to user questions with basic prompts
Phase 1.5User skips discussionNoProceed with seed_analysis as-is
Phase 1.5Max rounds reached (5)NoForce confirmation with current state
Phase 2Single CLI perspective failsNoContinue with available perspectives
Phase 2All CLI calls failNoGenerate basic brief from seed analysis
Phase 3Gemini CLI failsNoUse codex fallback
Phase 4Architecture review failsNoSkip review, proceed with initial analysis
Phase 5Story generation failsNoGenerate epics without detailed stories
Phase 6Validation CLI failsNoGenerate partial report with available data
Phase 6.5Auto-fix CLI failsNoLog failure, proceed to handoff with Review status
Phase 6.5Max iterations reachedNoForce handoff, report remaining issues
CLI Fallback Chain

Gemini -> Codex -> Claude -> degraded mode (local analysis only)

© catlog22, MIT. 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 19 other files in .claude/skills/spec-generator of catlog22/Claude-Code-Workflow.

  • SKILL.md
  • README.md
  • phases/01-5-requirement-clarification.md
  • phases/01-discovery.md
  • phases/02-product-brief.md
  • phases/03-requirements.md
  • phases/04-architecture.md
  • phases/05-epics-stories.md
  • phases/06-5-auto-fix.md
  • phases/06-readiness-check.md
  • specs/document-standards.md
  • specs/glossary-template.json
  • specs/quality-gates.md
  • templates/architecture-doc.md
  • templates/epics-template.md
  • templates/product-brief.md
  • templates/profiles/api-profile.md
  • … and 3 more

Open the folder on GitHubat commit 07491b0

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Questions about Spec Generator

What does Spec Generator do?

Specification generator - 7 phase document chain producing product brief, PRD, architecture, epics, and issues with Codex review gates. Spec Generator is an agent skill from catlog22/Claude-Code-Workflow. Specification generator - 7 phase document chain producing product brief, PRD, architecture, epics, and issues with Codex review gates.

When should I use Spec Generator?

Spec Generator fits situations like: create specification; tasks that involve User stories; tasks that involve PRD writing.

How do I install Spec Generator in Claude Code?

Run `npx skills add catlog22/Claude-Code-Workflow --skill spec-generator -a claude-code`. Or copy the skill folder (.claude/skills/spec-generator in catlog22/Claude-Code-Workflow) into .claude/skills/spec-generator in your project. Claude Code loads it when a task matches its description.

How do I install Spec Generator in Codex?

Run `npx skills add catlog22/Claude-Code-Workflow --skill spec-generator -a codex`. Or copy the skill folder (.claude/skills/spec-generator in catlog22/Claude-Code-Workflow) into .agents/skills/spec-generator in your project. Codex loads it when a task matches its description.

Can I use Spec Generator 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 catlog22/Claude-Code-Workflow --skill spec-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/spec-generator, .gemini/skills/spec-generator, .github/skills/spec-generator and .opencode/skills/spec-generator in your project.

What does Spec Generator need to run?

SKILL.md names no scripts, command-line tools or credentials: Spec Generator is instructions for the agent only. Its frontmatter pre-approves these tools: Agent, AskUserQuestion, TaskCreate, TaskUpdate, TaskList, Read, Write, Edit, Bash, Glob, Grep, Skill.

Does Spec Generator 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 Spec Generator 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. Review the folder before installing.

What licence does Spec Generator use?

Spec Generator 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 Spec Generator use?

About 4.3k tokens (SKILL.md is roughly 17k 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 Spec Generator?

Skills that share tags, products or a category with Spec Generator: Ralph Tui Create Beads (subsy/ralph-tui, 2.5k stars), Ralph Tui Create Beads Rust (subsy/ralph-tui, 2.5k stars), Ralph Tui Create JSON (subsy/ralph-tui, 2.5k stars) and To Prd (ywwynm/EverythingDone, 144 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Spec Generator?

catlog22 (a GitHub user) maintains it in catlog22/Claude-Code-Workflow, which has 2,130 GitHub stars. The repository holds 82 skills in this directory. The repository was last updated on June 18, 2026.

Source: catlog22/Claude-Code-Workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.