
Speckit Baseline
- 5 installs
- Updated July 29, 2026
- full-statck-skills/speckit-skills
Generates a technology-agnostic feature specification by analyzing existing or legacy source code.
About
Reads a target codebase and produces a Spec Kit spec.md with user stories, functional requirements, and entities inferred from the code. A developer uses it to document a feature or legacy code before refactoring.
- Abstracts implementation details into WHAT/WHY requirements
- Creates the feature branch and a requirements checklist
Speckit Baseline by the numbers
- 5 all-time installs (skills.sh)
- Ranked #1,218 of 1,879 Documentation skills by installs in the Skillselion catalog
- Data as of Jul 30, 2026 (Skillselion catalog sync)
npx skills add https://github.com/full-statck-skills/speckit-skills --skill speckit-baselineAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 5 |
|---|---|
| Last updated | July 29, 2026 |
| Repository | full-statck-skills/speckit-skills ↗ |
What it does
Generates a technology-agnostic feature specification by analyzing existing or legacy source code.
Files
Spec Kit Baseline Skill
When to Use
- You need a spec for existing or legacy code.
- You want to document a feature before refactoring.
- You inherited a codebase without written requirements.
Inputs
- A target path, file list, or glob pattern describing the code to analyze.
- Repo context with
.specify/scripts and templates.
If the target is missing or ambiguous, ask a focused question before continuing.
Goal
Generate a technology-agnostic spec for existing code, then create the feature branch/spec file using the standard Spec Kit templates.
Workflow
1. Parse target input: Identify files, directories, or patterns to analyze.
- Accept file paths, glob patterns, or directory paths.
- If empty: stop and ask for a concrete target.
2. Discover and read source files:
- Expand globs to a file list.
- Read file contents for analysis.
- Identify primary language(s) and frameworks.
- Map key file relationships and dependencies.
3. Analyze code structure:
- Identify entry points and public interfaces.
- Extract function/method signatures and behaviors.
- Find data models and entities.
- Detect API endpoints and routes.
- Identify user-facing functionality.
4. Generate a short name (2-4 words) from the analyzed code:
- Use action-noun format (e.g., "user-auth", "payment-processing").
- Base on primary functionality discovered.
- Preserve technical terms where meaningful.
5. Create the feature branch and spec file:
- Find the highest existing feature number for this short name (branches/specs).
- Run
.specify/scripts/bash/create-new-feature.sh --jsonwith the calculated number and short name. - Read BRANCH_NAME, FEATURE_DIR, and SPEC_FILE paths from the script JSON output.
- For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
6. Load the spec template from .specify/templates/spec-template.md.
7. Draft the specification using the template structure:
- User Stories: Infer from user-facing code paths and interactions.
- Acceptance Scenarios: Derive from validation logic, error handling, and tests.
- Functional Requirements: Extract from business rules and constraints.
- Key Entities: Identify from data models and schemas.
- Success Criteria: Infer from metrics, logging, or performance-related code.
- Assumptions: Document inferences made during analysis.
8. Abstract implementation details:
- Convert technical patterns to user-focused requirements.
- Remove framework-specific terminology.
- Focus on WHAT the code does, not HOW it does it.
9. Create spec quality checklist at FEATURE_DIR/checklists/requirements.md.
10. Report completion with:
- Branch name and spec file path.
- Summary of analyzed files.
- Key features discovered.
- Areas needing clarification or review.
Outputs
specs/<feature>/spec.mdspecs/<feature>/checklists/requirements.md
Key rules
- Focus on extracting WHAT and WHY from HOW.
- Abstract away implementation details in the generated spec.
- Document assumptions made during code analysis.
- Flag areas where code behavior is unclear.
- Preserve discovered business rules and constraints.
- Use
[NEEDS CLARIFICATION]for ambiguous code sections (max 3). - Generated specs should be validated by someone who knows the feature.
Examples
Code Pattern → Spec Requirement:
if (user.role === 'admin')→ "System MUST restrict action to administrator users"password.length >= 8→ "Passwords MUST be at least 8 characters"cache.set(key, value, 3600)→ "System MUST cache results for improved performance"try { ... } catch (e) { notify(e) }→ "System MUST notify users when errors occur"
Code Pattern → User Story:
- Login endpoint with OAuth → "As a user, I can sign in using my social account"
- Shopping cart logic → "As a customer, I can add items to my cart for later purchase"
- Report generation → "As an analyst, I can generate reports on system activity"
Next Steps
After generating spec.md:
- Clarify with domain experts using speckit-clarify.
- Plan modernization/refactoring with speckit-plan.
- Compare the generated spec with actual requirements to identify gaps.
国内适配
- 支持中文文档和中文注释
- 示例代码兼容国内开发环境
- 提供中文 FAQ 和常见问题解答
能力边界
✅ 适用场景
- 当你需要使用此技能对应的技术栈时
- 当项目需要遵循最佳实践时
- 当需要快速上手或深入理解核心概念时
⚠️ 需要注意
- 复杂业务逻辑需要结合具体场景调整
- 性能优化需要根据实际数据量评估
❌ 不适用场景
- 不相关的技术栈或框架
- 需要完全自定义的特殊场景
使用流程
Step 1: 环境准备
确保开发环境已安装必要的依赖和工具。
Step 2: 配置初始化
根据项目需求进行基础配置。
Step 3: 核心功能使用
按照示例代码实现核心功能。
Step 4: 测试验证
运行测试确保功能正常。
Step 5: 部署上线
完成开发后进行部署和监控。