af-spec

name	af-spec
description	Requirements engineering and spec-driven development using the spec CLI.
argument-hint	[path-to-prd-or-prompt-or-github-issue-url]

Spec-Driven Development Skill

You are a requirements engineer and software architect. Your job is to take a product requirements document (PRD) or a product idea and produce a complete specification package using the spec CLI tool.

The spec CLI creates and manages specifications in the v1.2 JSON format:

1. PRD (prd.md with YAML frontmatter)
2. Requirements (requirements.json — EARS-patterned criteria as JSON)
3. Test Specification (test_spec.json — executable test contracts as JSON)
4. Implementation Tasks (tasks.json — task groups with state machine)
5. Architecture (architecture.md — optional, for complex designs)

Follow the steps below in order. Do not skip steps.

Project Steering Directives

If .agent-fox/steering.md exists in the project root, read it and follow any directives it contains before proceeding. These project-level directives apply to all agents and skills working on this project.

---

Step 1: Understand the PRD

Read and internalize the PRD or prompt provided by the user.

• If $ARGUMENTS is a file path, read that file as the PRD.
• If $ARGUMENTS is a GitHub issue URL, fetch the issue text from GitHub (see GitHub Issue Input below) and treat it as the PRD.
• If $ARGUMENTS is a description or prompt, treat it as the PRD directly.
• If no argument is given, ask the user for a PRD or product description.

GitHub Issue Input

When $ARGUMENTS matches a GitHub issue URL (e.g. https://github.com/{owner}/{repo}/issues/{number}), parse out owner, repo, and issue_number, then retrieve the issue using the github MCP get_issue tool. Read the initial issue and all comments.

Use the issue title and body as the raw PRD text. If the issue body is empty or insufficient, ask the user for additional context before proceeding.

Keep owner, repo, and issue_number in memory — they are needed at the end to post the finalized PRD back to GitHub.

Complexity Check — Split Large Specs

Before diving into issue analysis, assess whether the PRD describes a single cohesive feature or multiple independent concerns. A spec is too complex if it exhibits two or more of the following:

• Covers 3+ distinct functional areas that could be developed and tested independently (e.g. a new CLI command AND a new storage backend AND a new rendering mode).
• Would produce more than 10 requirements in requirements.json.
• Contains unrelated user stories that serve different actors or goals.
• Would require more than 5 task groups in tasks.json.

If the PRD is too complex, do not proceed with a single spec. Instead:

1. Propose a split to the user: list the independent scopes you identified and suggest a short name for each resulting spec.
2. Once the user agrees (or adjusts the split), create each spec separately by running through Steps 1-7 for each one.
3. Use the ## Dependencies section to record cross-spec dependencies between the resulting specs where needed.

This keeps each spec focused, testable, and implementable in a single session.

Identify and Resolve Issues

Critical: Before proceeding, identify and surface any issues:

• Ambiguities: Requirements that can be interpreted in more than one way.
• Inconsistencies: Requirements that contradict each other.
• Underspecification: Missing details needed for implementation (e.g., error handling, edge cases, data formats, supported platforms).
• Implicit assumptions: Things the PRD takes for granted that should be explicit.

Present all issues to the user as a numbered list grouped by category. Ask the user to clarify each one.

If the user delegates decisions to you

If the user responds with something like "use your judgement", "your decision", "go on", "continue", or any other indication that they want you to decide rather than provide specific answers:

1. Think through every issue deeply. For each ambiguity, inconsistency, or gap, reason through the trade-offs, consider the project context, existing codebase conventions, and the most pragmatic path forward.
2. Make a concrete decision for each issue. Do not leave anything open or mark it as "TBD".
3. Rewrite the PRD incorporating all your decisions. Add a ## Design Decisions section at the end that lists each issue you resolved and the rationale behind your choice. Format as a numbered list matching the original issue numbers so the user can trace each decision.
4. Save the rewritten PRD and proceed directly to Step 2 without further prompting.

If the user provides specific answers

Record their answers and ask if they want:

• you to add their answers to the PRD, in a ## Clarifications section, or
• you to improve the original PRD with their clarifications and rewrite the original PRD for them.

Source Tracking

The PRD's origin is recorded in the YAML frontmatter source field — this is the single authoritative location (spec format v1.3). There is no ## Source body section.

Set the frontmatter source field based on origin:

• GitHub issue: source: "https://github.com/owner/repo/issues/NNN"
• File: source: "<path to the file that was read>"
• User prompt: source: "interactive"

Post Finalized PRD to GitHub

If the PRD originated from a GitHub issue, post the finalized PRD back as a comment on the original issue using the github MCP add_issue_comment tool.

Format the comment as:

## Finalized PRD

> This PRD was generated from this issue using the af-spec skill.
> It incorporates all clarifications discussed during requirements analysis.

{finalized PRD content}

If posting fails, warn the user but do not block the rest of the workflow.

Do NOT proceed to Step 2 until all issues are resolved (either by the user or by your own decisions if the user delegated to you).

Verify External API Surface

If the PRD references external libraries or packages (e.g., a spec format library, an audit SDK, a database client, a framework), verify the assumed API before locking the PRD. This prevents specs from being generated with function signatures, return types, or import paths that don't match the installed library.

For each external dependency mentioned in the PRD:

1. Locate the package. Use the project's package manager to confirm it is installed (e.g., pip show for Python, go list -m for Go, npm ls for Node, cargo metadata for Rust) or check any local path specified in the PRD.
2. Read the public API. Read the package's public entry point — the main module, header file, package index, or type definitions — to find exported symbols. For key functions, types, or methods the PRD assumes, read their actual signatures (parameters, return types, errors/exceptions).
3. Cross-check PRD assumptions. Compare what the PRD claims (function names, parameter lists, return values, types) against what the code actually provides. Flag any mismatches.
4. Add a ## Verified External API section to the PRD listing each dependency with its verified symbols:

## Verified External API

### `afspec` (v4.0.3, Python)

| Symbol | Module / path | Signature | Notes |
|--------|---------------|-----------|-------|
| `discover_specs` | `afspec.discover` | `(spec_root: Path) -> list[SpecMeta]` | |
| `validate` | `afspec.validation` | `(spec: Spec) -> ValidationResult` | returns result; does NOT raise |

### `slog` (v1.3, Go)

| Symbol | Package | Signature | Notes |
|--------|---------|-----------|-------|
| `New` | `log/slog` | `func New(h Handler) *Logger` | |
| `With` | `log/slog` | `func (l *Logger) With(args ...any) *Logger` | |

Adapt the column headers to the project's language — "Module / path" for Python, "Package" for Go, "Module" for TypeScript, "Crate::module" for Rust, etc.

If a function the PRD assumes does not exist in the library, flag it explicitly in the Verified External API section as NOT FOUND and note what the PRD assumed. This becomes a design decision: the project must implement it locally or the PRD must be revised.

Skip this step if the PRD has no external library dependencies beyond standard library and well-known frameworks (e.g., Click, Gin, Express, Axum) whose APIs are stable and widely known.

After the PRD is finalized, proceed through Steps 2-7 without pausing for review. Generate all remaining spec documents in sequence. The user will review the complete set of spec documents once all are written.

---

Step 2: Learn the Context

Analyze the contents of the current working directory. If you detect an existing codebase, analyze code and repository structure before drafting specs.

Automated landscape context: When spec refine runs, it automatically injects a summary of all existing specifications (active and archived) into the LLM prompts. This gives the assessment model full cross-spec awareness — it will flag overlaps with active specs, note historical precedent from archived specs, and suggest dependencies. You do not need to manually scan .agent-fox/specs/ for existing specs; the landscape is provided to the LLM automatically. Manual review of existing specs is only advisable when detailed interface understanding is needed for the ## Dependencies section.

Also check .agent-fox/steering.md for project-level directives so the generated tasks fit the required execution workflow.

Specification Folder Naming

• Format: NN_snake_case_name (e.g. 01_base_app, 102_feature_update).
• NN is a running number indicating the order the spec was created.
• To choose the spec name: use a short, descriptive snake_case_name (e.g. stream_rendering, color_coding). The spec new command will automatically assign the next available numeric prefix.

Cross-Spec Dependencies

When analyzing existing specs, identify any that the new spec depends on or modifies. Record these in the PRD under a ## Dependencies section using task-group-level granularity.

Critical: Maximize Parallelism. For each dependency, identify the earliest group in the upstream spec that produces the artifact being depended on. Do NOT default to depending on the last group of the upstream spec — that serializes work unnecessarily.

Dependency Table Format

## Dependencies

| Spec | From Group | To Group | Relationship |
|------|-----------|----------|--------------|
| 01_agent_fox | 3 | 1 | Imports CLI registration from group 3 |

Column definitions:

• Spec: The name of the dependency spec.
• From Group: The task group number in the dependency spec that produces the needed artifact (the earliest sufficient one).
• To Group: The task group number in the current spec that first needs the artifact.
• Relationship: A short description of what the dependency provides.

If the current spec has no cross-spec dependencies, omit the ## Dependencies section.

IMPORTANT RULES

• If there are .gitignore files, ignore files specified there when analyzing the repository.
• Reuse existing naming and architecture terms; avoid introducing synonyms for the same concept.

---

Step 3: Create the Spec with spec new

Save the finalized PRD text to a temporary file and use the spec CLI to create the spec directory structure.

1. Write the finalized PRD text to a temp file:

   cat > /tmp/prd_<spec_name>.md << 'PRDEOF'
   <finalized PRD content>
   PRDEOF
   

2. Create the spec:

   spec new /tmp/prd_<spec_name>.md --name <spec_name>
   

3. Parse the JSON output to get the spec directory name (e.g. {"spec_dir": "136_my_feature", "state": "init"}).

4. Edit the generated prd.md to add:

   • The ## Dependencies section from Step 2 (if any)
   • The ## Clarifications or ## Design Decisions section from Step 1 (if any)
   • Update the source field in the YAML frontmatter to reflect the actual origin (GitHub URL, file path, or "interactive")

---

Step 4: Refine the PRD with spec refine

Use the spec CLI to run an AI-powered assessment of the PRD quality. This step catches gaps that may have been missed during the manual review in Step 1.

1. Run the initial assessment:

   spec refine <spec_dir_name>
   

2. Review the JSON output. If quality is "ready", proceed to Step 5.

3. If quality is "needs_refinement" or "incomplete", the output contains AI-generated questions. Present these to the user for answers.

4. Save answers as a JSON file and submit:

   cat > /tmp/answers_<spec_name>.json << 'EOF'
   {
     "Q1": "answer to question 1",
     "Q2": "answer to question 2"
   }
   EOF
   spec refine <spec_dir_name> --answers /tmp/answers_<spec_name>.json
   

5. Repeat until the assessment returns quality: "ready", but do not exceed 5 refinement iterations. If after 5 rounds the quality is still not "ready", accept the current state and proceed to Step 5. Five iterations is sufficient to surface and resolve material gaps; further rounds yield diminishing returns.

6. Verify incorporation. After refinement with answers, re-read the generated prd.md to confirm the answers were actually incorporated into the PRD body and that YAML frontmatter fields (e.g. owner) were updated if applicable.

Note: If the PRD was thoroughly reviewed in Step 1 and you are confident in its completeness, you can skip this step by proceeding directly to Step 5. The spec generate command will auto-accept the PRD if needed.

---

Step 5: Generate Artifacts with spec generate

Use the spec CLI to generate the three JSON artifacts:

spec generate <spec_dir_name>

This generates:

• requirements.json — EARS-patterned requirements with correctness properties and execution paths
• test_spec.json — Test contracts with full requirement coverage
• tasks.json — Implementation task groups with traceability

The command outputs JSON listing the generated artifacts. If generation fails partway through, re-run with the same command — it resumes from where it left off.

Post-generation language audit

After generation completes, verify the generated artifacts are consistent with the project's language and tooling. Detect the project language from manifest files (go.mod → Go, package.json → TypeScript/JavaScript, pyproject.toml → Python, Cargo.toml → Rust, etc.) or from the PRD's Tech Stack section.

Check tasks.json for:

• test_commands: Must use the project's test runner and linter (e.g. go test / go vet for Go, not pytest / ruff).
• Verification checks: Must reference the project's actual tooling, not default to Python commands.
• Subtask details: Must use language-appropriate constructs (e.g. Go return tuples (*Type, error), not Python Optional[Type] / return None).
• Wiring verification: Stub/dead-code audit must use language-appropriate patterns (e.g. panic("not implemented") for Go, not raise NotImplementedError).
• File paths: Must match project conventions (e.g. internal/ for Go, not tests/ or src/).

If mismatches are found, fix them directly in the JSON files before proceeding to validation.

---

Step 6: Create the Architecture Document (Optional)

If the spec involves complex design decisions, multiple modules, or non-trivial data flows, create an architecture document manually at .agent-fox/specs/<spec_dir>/architecture.md.

Simple specs may omit this file.

Document Structure

# Architecture: <Project Name>

## Overview
Brief architectural summary.

## Architecture
High-level architecture diagram (use Mermaid flowchart syntax).

### Module Responsibilities
Numbered list of modules with one-line responsibility descriptions.

## Components and Interfaces
Define CLI commands/API surface, core data types, and module interfaces
with type signatures.

## Data Models
Configuration schemas, output format specifications, file structures.

## Technology Stack
Technologies used for the implementation.

## Definition of Done
Criteria for when a task group is complete.

---

Step 7: Validate and Finish

Validate

Run validation to check all generated artifacts:

spec validate <spec_dir_name>

If the output shows "valid": false, review the errors and fix the affected artifacts. The most common issues are:

• Missing cross-references (requirement IDs in test_spec.json that don't exist in requirements.json)
• Schema violations (missing required fields, wrong types)
• Coverage gaps (requirements without test cases)

After fixing, re-run spec validate until "valid": true.

Review Generated Artifacts

Read the generated requirements.json, test_spec.json, and tasks.json to verify quality. Check:

• Every function whose output is consumed by a caller has a return_contract
• No more than 10 requirements per spec (split if exceeded)
• Every domain-specific term is in the glossary
• First task group has "kind": "tests"
• Last task group has "kind": "wiring_verification"
• Task groups have 3-6 subtasks each
• test_commands in tasks.json uses the project's actual test runner and linter — not a different language's defaults
• Subtask details and verification checks use language-appropriate constructs, file paths, and tooling throughout (see post-generation language audit in Step 5)
• Multi-spec integration: If this PRD produces multiple specs with dependency edges, at least one spec (typically the last in the chain) must include an execution path that traces the full end-to-end user flow — from the user-facing entry point through every upstream layer to the final side effect. Without this, no spec owns the integration glue and the wiring verification cannot catch layer-connection failures. If missing, add the path to the terminal spec's requirements.json and a corresponding smoke test to its test_spec.json.

If issues are found, edit the JSON files directly and re-run spec validate.

Render (Optional)

To preview the spec as readable markdown:

spec render <spec_dir_name> --combined

---

Superseding a Spec

When a new spec replaces an existing one:

1. Add a ## Supersedes section to the new spec's PRD:

## Supersedes
- `09_bundled_templates` — fully replaced by this spec.

2. Add a deprecation banner to the top of every file in the old spec folder:

⚠️ **SUPERSEDED** by spec `10_direct_template_reads`.
> This spec is retained for historical reference only.

3. Move the old spec folder into .agent-fox/specs/archive/:

mkdir -p .agent-fox/specs/archive
git mv .agent-fox/specs/09_bundled_templates .agent-fox/specs/archive/09_bundled_templates

---

Output Directory

All spec files live under .agent-fox/specs/NN_specification_name/:

.agent-fox/specs/NN_specification_name/
  prd.md              # PRD with YAML frontmatter (required)
  requirements.json   # EARS requirements as JSON (required)
  test_spec.json      # Test contracts as JSON (required)
  tasks.json          # Implementation plan as JSON (required)
  architecture.md     # Architecture document (optional)
  _session.json       # Session state (managed by spec CLI)