Test Researcher
A8.0Researches real-world problems and edge cases before test planning to ensure tests cover actual user pain points, not just AC.
Get This Skill on GitHubOverview
name: ln-511-test-researcher description: Researches real-world problems, competitor solutions, and customer complaints before test planning. Posts findings as Linear comment for ln-512 and ln-513.
Test Researcher
Researches real-world problems and edge cases before test planning to ensure tests cover actual user pain points, not just AC.
Purpose & Scope
- 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.
When to Use
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
Workflow
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
- Fetch Story from Linear
- 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")
- Extract keywords for research queries
Phase 3: Research Common Problems
Use available tools to find real-world problems:
-
Web Search:
- "[feature] common problems"
- "[format] edge cases"
- "[API] gotchas"
- "[technology] known issues"
-
MCP Ref:
ref_search_documentation("[feature] error handling best practices")ref_search_documentation("[format] validation rules")
-
Context7:
- Query relevant library docs for known issues
- Check API documentation for limitations
Phase 4: Research Competitor Solutions
-
Web Search:
- "[competitor] [feature] how it works"
- "[feature] comparison"
- "[product type] best practices"
-
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
-
Web Search:
- "[feature] complaints"
- "[product type] user problems"
- "[format] issues reddit"
- "[format] issues stackoverflow"
-
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
-
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)
-
Post Linear comment on Story with research summary:
## Test Research: {Feature}
### 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)._
Critical Rules
- 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".
Definition of Done
- 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.
Reference Files
- 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
Version: 1.0.0 (Initial release - extracted from ln-503-manual-tester Phase 0) Last Updated: 2026-01-15
What This Skill Can Do
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