gitlink-cli/docs/competition-solution.md

GitLink CLI Agent Workflow Enhancement Suite

1. Background

GitLink CLI serves both human maintainers and AI Agents. The competition focuses on intelligent open-source contribution workflows, where structured analysis, stable output, and safe automation matter more than raw command count.

2. Problem

Open-source maintenance often suffers from:

• Issue backlog and delayed triage
• High PR review cost
• Repetitive release note preparation
• Lack of structured repository health evaluation
• AI Agents needing stable, machine-readable output

3. Solution

This project extends GitLink CLI with the GitLink CLI Agent Workflow Enhancement Suite.

Implemented now:

• workflow +triage
• workflow +health
• workflow +pr-summary
• read-only GitLink fetch layer for workflow triage and health
• read-only PR metadata, changed files, and commits fetch layer for PR summary
• expanded fetch boundary tests for empty responses, label and author normalization, error-in-body handling, alternative activity timestamps, release shapes, and CI unavailability
• local-first analysis with no LLM dependency
• stable Agent-facing JSON / table / markdown output

Planned next:

• workflow +release-notes
• workflow +stale

4. Technical Route

• Go + Cobra + existing shortcut architecture
• rule-based analysis
• stable DTOs
• json / table / markdown renderers
• en / zh-CN message mapping
• no LLM dependency
• local-first, dry-run-safe workflow design

5. Implemented Features

workflow +triage

• issue type detection
• priority scoring
• confidence scoring
• missing information detection
• risk flags
• recommended action
• suggested comment
• reasoning and matched rules

workflow +health

• health score
• risk level
• metrics
• scoring notes
• recommendations
• unknown metric tolerance

workflow +pr-summary

• change type detection
• risk level analysis
• review focus generation
• test suggestion generation
• merge checklist generation
• read-only fetch of PR metadata, changed files, and commits

6. Innovation Points

• Agent-native structured output
• rule-based intelligence without external LLM dependency
• explainable workflow decisions
• safety-first local analysis
• bilingual command output
• extensible workflow command design
• competition-friendly incremental PR path

7. Testing and Verification

• Unit tests cover triage, health scoring, messages, rendering, and command helpers.
• Fetch-layer tests cover issue normalization, repository health probing, and PR metadata/file/commit normalization with httptest.
• Boundary tests cover empty responses, label and author normalization, error-in-body handling, alternative activity timestamps, release response shapes, and CI unavailability.
• PR summary tests cover docs-only, workflow code, internal client, security-sensitive, mixed-file, zh-CN, render, command, and fetch-failure cases.
• Local command examples were executed successfully.
• Full repository testing passed in the current environment.
• Automated tests use httptest and do not depend on real remote API availability.

8. Demonstration Plan

Official repository

Use Gitlink/gitlink-cli as the reference repository:

1. workflow +triage with English table output
2. workflow +triage with security JSON output
3. workflow +triage with Chinese markdown output
4. workflow +health with table output
5. workflow +health with risky JSON output
6. workflow +pr-summary with markdown output
7. Explain how agents consume stable JSON

Self-built test repository

Use a small demo repository to show:

• bug triage
• security triage
• docs triage
• healthy repo score
• risky repo score

9. Roadmap

• Phase 1: local workflow prototype, completed
• Phase 2: API fetch and normalization, completed
• Phase 3: pr-summary, completed
• Phase 4: release-notes, stale

10. PR Plan

• PR 1: workflow rule engine and local commands
• PR 2: documentation and tests
• PR 3: API fetch layer
• PR 4: pr-summary
• PR 5: release-notes / stale