ln-511-test-researcher

• Research common problems for the feature domain using Web Search, MCP Ref, Context7.
• Analyze how competitors solve the same problem.
• Find customer complaints and pain points from forums, StackOverflow, Reddit.
• Post structured findings as Linear comment for downstream skills (ln-512, ln-513).
• No test creation or status changes.

This skill should be used when:

• Invoked by ln-510-test-planner at start of test planning pipeline
• Story has non-trivial functionality (external APIs, file formats, authentication)
• Need to discover edge cases beyond AC

Skip research when:

• Story is trivial (simple CRUD, no external dependencies)
• Research comment already exists on Story
• User explicitly requests to skip

Phase 1: Discovery

Auto-discover Team ID from docs/tasks/kanban_board.md.

Input: Story ID from orchestrator (ln-510)

Phase 2: Extract Feature Domain

1) Fetch Story from Linear

2) Parse Story goal and AC to identify:

- What technology/API/format is involved?

- What is the user's goal? (e.g., "translate XLIFF files", "authenticate via OAuth")

3) Extract keywords for research queries

Phase 3: Research Common Problems

Use available tools to find real-world problems:

1) Web Search:

- "[feature] common problems"

- "[format] edge cases"

- "[API] gotchas"

- "[technology] known issues"

2) MCP Ref:

- ref_search_documentation("[feature] error handling best practices")

- ref_search_documentation("[format] validation rules")

3) Context7:

- Query relevant library docs for known issues

- Check API documentation for limitations

Phase 4: Research Competitor Solutions

1) Web Search:

- "[competitor] [feature] how it works"

- "[feature] comparison"

- "[product type] best practices"

2) Analysis:

- How do market leaders handle this functionality?

- What UX patterns do they use?

- What error handling approaches are common?

Phase 5: Research Customer Complaints

1) Web Search:

- "[feature] complaints"

- "[product type] user problems"

- "[format] issues reddit"

- "[format] issues stackoverflow"

2) Analysis:

- What do users actually struggle with?

- What are common frustrations?

- What gaps exist between user expectations and typical implementations?

Phase 6: Compile and Post Findings

1) Compile findings into categories:

- Input validation issues (malformed data, encoding, size limits)

- Edge cases (empty input, special characters, Unicode)

- Error handling (timeouts, rate limits, partial failures)

- Security concerns (injection, authentication bypass)

- Competitor advantages (features we should match or exceed)

- Customer pain points (problems users actually complain about)

2) Post Linear comment on Story with research summary:

```markdown

Sources Consulted

• [Source 1](url)
• [Source 2](url)

Common Problems Found

1. Problem 1: Description + test case suggestion
2. Problem 2: Description + test case suggestion

Competitor Analysis

• Competitor A: How they handle this + what we can learn
• Competitor B: Their approach + gaps we can exploit

Customer Pain Points

• Complaint 1: What users struggle with + test to prevent
• Complaint 2: Common frustration + how to verify we solve it

Recommended Test Coverage

• [ ] Test case for problem 1
• [ ] Test case for competitor parity
• [ ] Test case for customer pain point

---

_This research informs both manual tests (ln-512) and automated tests (ln-513)._

```

• No test creation: Only research and documentation.
• No status changes: Only Linear comment.
• Source attribution: Always include URLs for sources consulted.
• Actionable findings: Each problem should suggest a test case.
• Skip trivial Stories: Don't research "Add button to page".

• [ ] Feature domain extracted from Story (technology/API/format identified)
• [ ] Common problems researched (Web Search + MCP Ref + Context7)
• [ ] Competitor solutions analyzed (at least 1-2 competitors)
• [ ] Customer complaints found (forums, StackOverflow, Reddit)
• [ ] Findings compiled into categories
• [ ] Linear comment posted with "## Test Research: {Feature}" header
• [ ] At least 3 recommended test cases suggested

Output: Linear comment with research findings for ln-512 and ln-513 to use.

• Research methodology: Web Search, MCP Ref, Context7 tools
• Comment format: Structured markdown with sources
• Downstream consumers: ln-512-manual-tester, ln-513-auto-test-planner

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Version: 1.0.0 (Initial release - extracted from ln-503-manual-tester Phase 0)

Last Updated: 2026-01-15