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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-baseline

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Listed on Skillselion
Installs5
Last updatedJuly 29, 2026
Repositoryfull-statck-skills/speckit-skills

What it does

Generates a technology-agnostic feature specification by analyzing existing or legacy source code.

Files

SKILL.mdMarkdownGitHub ↗

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 --json with 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.md
  • specs/<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。

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