ac-spec-parser
Parse and validate project specifications. Use when loading YAML/JSON specs, validating spec structure, extracting requirements, or converting between spec formats.
Best use case
ac-spec-parser is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Parse and validate project specifications. Use when loading YAML/JSON specs, validating spec structure, extracting requirements, or converting between spec formats.
Teams using ac-spec-parser should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ac-spec-parser/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ac-spec-parser Compares
| Feature / Agent | ac-spec-parser | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Parse and validate project specifications. Use when loading YAML/JSON specs, validating spec structure, extracting requirements, or converting between spec formats.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# AC Spec Parser
Parse and validate project specifications for autonomous coding.
## Purpose
Parses YAML/JSON/Markdown specifications into structured data for feature generation and planning.
## Quick Start
```python
from scripts.spec_parser import SpecParser
parser = SpecParser(project_dir)
spec = await parser.parse("spec.yaml")
print(spec.project_name)
print(spec.requirements)
```
## Supported Formats
- **YAML**: `.yaml`, `.yml` - Structured specifications
- **JSON**: `.json` - Machine-readable specs
- **Markdown**: `.md` - Human-readable specs with sections
## Specification Schema
```yaml
project:
name: "Project Name"
description: "What the project does"
type: "web-app|api|cli|library"
requirements:
functional:
- id: "REQ-001"
description: "User can login"
priority: "high|medium|low"
acceptance_criteria:
- "Valid credentials grant access"
- "Invalid credentials show error"
non_functional:
- id: "NFR-001"
description: "Response under 200ms"
category: "performance|security|usability"
technology:
language: "python|typescript|go"
framework: "fastapi|nextjs|gin"
database: "postgresql|mongodb"
constraints:
- "Must run on AWS"
- "Budget under $100/month"
```
## Workflow
1. **Load**: Read spec file from disk
2. **Parse**: Convert to structured data
3. **Validate**: Check required fields and schema
4. **Normalize**: Standardize format for downstream use
5. **Export**: Output to feature analyzer
## Validation Rules
- Project name required
- At least one functional requirement
- All requirements have unique IDs
- Priority values are valid
- Technology stack is coherent
## Integration
Used by:
- `ac-spec-generator`: Generates feature list from parsed spec
- `ac-feature-analyzer`: Analyzes requirements
- `ac-complexity-assessor`: Estimates complexity
## API Reference
See `scripts/spec_parser.py` for full implementation.Related Skills
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