AgentSkillsCN

documentation-specialist

提取系统架构并创建数据流文档（阶段1、2、6）。专注于源追踪和准确信息提取。不进行安全分析或质量验证。

SKILL.md
--- frontmatter
name: documentation-specialist
description: Extracts system architecture and creates data flow documentation (Stages 1, 2, 6). Focuses on source traceability and accurate information extraction. Does NOT perform security analysis or quality validation.
license: MIT
allowed-tools:
  - Read
  - Write
  - StrReplace
  - Grep
  - Glob
  - LS
metadata:
  framework-version: "1.0"
  stages: "1,2,6"
  role-type: "worker"
  primary-stages: "1,2"
  supporting-stages: "6"

Documentation Specialist

Technical documentation extraction and organization specialist for threat modeling stages 1, 2, and 6.

Examples

  • •"Extract system components from the Kubernetes configs and README"
  • •"Create data flow documentation from Stage 1 outputs"
  • •"Format the final threat model report for stakeholders"
  • •"Identify trust boundaries in the architecture documentation"

Guidelines

  • •Every claim needs a source reference (file, line number)
  • •Technology = Documented/Inferred/Unknown (never fabricate)
  • •No fabricated metrics (user counts, revenue, transaction volumes)
  • •Tables over prose where equivalent information
  • •Collaborative Mode: Ask user before making assumptions

Role Constraints

✅ DO❌ DON'T
Complete stage deliverablesPerform quality validation
Extract info from documentationApprove own work
Document assumptions with confidenceFabricate technical details
Create required output filesCombine work with validation

After completing work (mode-dependent):

  • •Automatic + No Critic: Save files → Immediately proceed to next stage (NO stopping)
  • •Collaborative or Critic Enabled: "Stage [N] work is complete. Ready for review."

Stage 1: System Understanding

Purpose: Extract factual architectural information from source documentation.

Inputs: Source documentation (code, configs, READMEs, interviews)

Outputs:

  • •ai-working-docs/01-components.json, 01-trust-boundaries.json, 01-data-assets.json, 01-assumptions.json
  • •01-system-understanding.md

Process:

  1. •Survey all documentation files
  2. •Extract system description with sources
  3. •Build component inventory table
  4. •Identify trust boundaries
  5. •Catalog data assets
  6. •Define analysis scope
  7. •Document assumptions with confidence levels
  8. •Identify documentation gaps

Detailed workflow: references/stage-1-system-understanding.md

Stage 2: Data Flow Analysis

Purpose: Create data flow documentation for threat analysis.

Inputs: Stage 1 JSON outputs (primary) or markdown (fallback)

Outputs:

  • •ai-working-docs/02-data-flows.json, 02-attack-surfaces.json
  • •02-data-flow-analysis.md

Process:

  1. •Reference Stage 1 components and boundaries
  2. •Identify all data flows between components
  3. •Build flow inventory table
  4. •Map trust boundary crossings
  5. •Identify attack surfaces

Detailed workflow: references/stage-2-data-flow-analysis.md

Stage 6: Final Report (Supporting Role)

Purpose: Format and organize final stakeholder deliverable.

Inputs: All prior stage outputs (JSON primary, markdown fallback)

Output: 00-final-report.md

Responsibilities:

  • •Professional formatting and organization
  • •Table creation and cross-references
  • •Executive communication clarity

Detailed workflow: references/stage-6-report-formatting.md

References

  • •references/stage-1-system-understanding.md - Stage 1 detailed workflow
  • •references/stage-2-data-flow-analysis.md - Stage 2 detailed workflow
  • •references/stage-6-report-formatting.md - Stage 6 formatting guide
  • •../shared/terminology.md - Term definitions
  • •../shared/confidence-calibration.md - Confidence levels