Agent skill

research-implement

Build a research definition and execute the study based on a Linear issue.

majiayu000534★ · 1 repos on radarProfile →
claude-codecan modify filesMIT
Install
npx skills add majiayu000/claude-skill-registry --skill research-implement --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 4 KB
Bundled scripts: none
Allowed tools: BashReadWriteEditGlobGrepmcp__linear__linear_getIssueByIdmcp__linear__linear_updateIssuemcp__linear__linear_createComment
Path: skills/analysis/research-implement/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Research Implementation Build a research study definition and execute it based on a Linear issue created by `/research-evaluate`. ## Usage ```bash /research-implement ENG-XXX ``` ## Workflow ### Step 1: Get Issue Details ```python issue = mcp__linear__linear_getIssueById(id="ENG-XXX") ``` Extract from description: - Source file path - Data requirements (assets, timeframe, period) - Methodology - Charts/tables to reproduce ### Step 2: Read Source Material ```bash # Read the source markdown file cat report_notes/<topic>/<source_file>.md ``` Understand: - Exact signal logic - Position sizing rules - Rebalancing frequency - Any special conditions ### Step 3: Update Issue Status ```python mcp__linear__linear_updateIssue( id="ENG-XXX", stateId="49c7285c-33c4-443c-a0af-49b51b8e1739" # In Progress ) ``` ### Step 4: Create Research Definition Create a JSON definition file following the study generation grammar. **File location:** `project/definitions/test_runner/<source_id>_research.json` **Template:** ```json { "name": "<source_id>_research", "type": "RESEARCH", "description": "<hypothesis from source>", "source_reference": { "id": "<source_id>", "url": "<source_url>", "title": "<source_

What's inside
Steps it walks through
  1. Usage
  2. Workflow
  3. Step 1: Get Issue Details
  4. Step 2: Read Source Material
  5. Step 3: Update Issue Status
  6. Step 4: Create Research Definition
  7. Step 5: Validate Definition
  8. Step 6: Build Job Data Binary (if needed)
  9. Step 7: Execute Study
  10. Step 8: Analyze Results
  11. Step 9: Compare with Source
  12. Step 10: Update Linear Issue
  13. Step 11: Update research.csv
  14. Definition Structure Reference
Ships with 1 file
  • metadata.json
Commands it runs
Read the source markdown file
cat report_notes/<topic>/<source_file>.md
cd /home/adesola/EpochDev/ClaudeCodeResearch
source .venv/bin/activate
Check JSON syntax
python -c "import json; json.load(open('project/definitions/test_runner/<source_id>_research.json'))"
Get tearsheet reports
Query data if needed
More from claude-skill-registry
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About this skill
What does the research-implement skill do?

Build a research definition and execute the study based on a Linear issue.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill research-implement --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going