skill-lean-research
Research Lean 4 and Mathlib for theorem proving tasks. Invoke for Lean-language research using LeanSearch, Loogle, and lean-lsp tools.
Best use case
skill-lean-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Research Lean 4 and Mathlib for theorem proving tasks. Invoke for Lean-language research using LeanSearch, Loogle, and lean-lsp tools.
Teams using skill-lean-research should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/skill-lean-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How skill-lean-research Compares
| Feature / Agent | skill-lean-research | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Research Lean 4 and Mathlib for theorem proving tasks. Invoke for Lean-language research using LeanSearch, Loogle, and lean-lsp tools.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Lean Research Skill
Thin wrapper that delegates Lean research to `lean-research-agent` subagent.
**IMPORTANT**: This skill implements the skill-internal postflight pattern. After the subagent returns,
this skill handles all postflight operations (status update, artifact linking, git commit) before returning.
## Trigger Conditions
This skill activates when:
- Task language is "lean4" or "lean" (either accepted)
- Research involves Mathlib, theorems, or proofs
- Lean-specific MCP tools are needed
---
## Execution Flow
### Stage 1: Input Validation
Validate required inputs:
- `task_number` - Must be provided and exist in state.json
- `focus_prompt` - Optional focus for research direction
```bash
# Lookup task
task_data=$(jq -r --argjson num "$task_number" \
'.active_projects[] | select(.project_number == $num)' \
specs/state.json)
# Validate exists
if [ -z "$task_data" ]; then
return error "Task $task_number not found"
fi
# Extract fields
language=$(echo "$task_data" | jq -r '.language // "general"')
status=$(echo "$task_data" | jq -r '.status')
project_name=$(echo "$task_data" | jq -r '.project_name')
description=$(echo "$task_data" | jq -r '.description // ""')
```
---
### Stage 2: Preflight Status Update
Update task status to "researching" BEFORE invoking subagent.
**Update state.json**:
```bash
jq --arg ts "$(date -u +%Y-%m-%dT%H:%M:%SZ)" \
--arg status "researching" \
--arg sid "$session_id" \
'(.active_projects[] | select(.project_number == '$task_number')) |= . + {
status: $status,
last_updated: $ts,
session_id: $sid
}' specs/state.json > specs/tmp/state.json && mv specs/tmp/state.json specs/state.json
```
**Update TODO.md**: Use Edit tool to change status marker from `[NOT STARTED]` or `[RESEARCHED]` to `[RESEARCHING]`.
---
### Stage 3: Prepare Delegation Context
Prepare delegation context for the subagent:
```json
{
"session_id": "sess_{timestamp}_{random}",
"delegation_depth": 1,
"delegation_path": ["orchestrator", "research", "skill-lean-research"],
"timeout": 3600,
"task_context": {
"task_number": N,
"task_name": "{project_name}",
"description": "{description}",
"language": "lean"
},
"focus_prompt": "{optional focus}",
"metadata_file_path": "specs/{N}_{SLUG}/.return-meta.json"
}
```
---
### Stage 4: Invoke Subagent
**CRITICAL**: You MUST use the **Task** tool to spawn the subagent.
**Required Tool Invocation**:
```
Tool: Task (NOT Skill)
Parameters:
- subagent_type: "lean-research-agent"
- prompt: [Include task_context, delegation_context, focus_prompt, metadata_file_path]
- description: "Execute Lean research for task {N}"
```
**DO NOT** use `Skill(lean-research-agent)` - this will FAIL.
The subagent will:
- Search Mathlib using lean_leansearch, lean_loogle, lean_leanfinder
- Verify theorems with lean_local_search and lean_hover_info
- Analyze findings and synthesize recommendations
- Create research report in `specs/{N}_{SLUG}/reports/`
- Write metadata to `specs/{N}_{SLUG}/.return-meta.json`
- Return a brief text summary (NOT JSON)
---
### Stage 5: Parse Subagent Return (Read Metadata File)
After subagent returns, read the metadata file:
```bash
metadata_file="specs/${padded_num}_${project_name}/.return-meta.json"
if [ -f "$metadata_file" ] && jq empty "$metadata_file" 2>/dev/null; then
status=$(jq -r '.status' "$metadata_file")
artifact_path=$(jq -r '.artifacts[0].path // ""' "$metadata_file")
artifact_type=$(jq -r '.artifacts[0].type // ""' "$metadata_file")
artifact_summary=$(jq -r '.artifacts[0].summary // ""' "$metadata_file")
else
echo "Error: Invalid or missing metadata file"
status="failed"
fi
```
---
### Stage 6: Update Task Status (Postflight)
If status is "researched", update state.json and TODO.md:
**Update state.json**:
```bash
jq --arg ts "$(date -u +%Y-%m-%dT%H:%M:%SZ)" \
--arg status "researched" \
'(.active_projects[] | select(.project_number == '$task_number')) |= . + {
status: $status,
last_updated: $ts,
researched: $ts
}' specs/state.json > specs/tmp/state.json && mv specs/tmp/state.json specs/state.json
```
**Update TODO.md**: Use Edit tool to change status marker from `[RESEARCHING]` to `[RESEARCHED]`.
**On partial/failed**: Keep status as "researching" for resume.
---
### Stage 7: Link Artifacts
Add artifact to state.json with summary.
```bash
if [ -n "$artifact_path" ]; then
jq --arg path "$artifact_path" \
--arg type "$artifact_type" \
--arg summary "$artifact_summary" \
'(.active_projects[] | select(.project_number == '$task_number')).artifacts += [{"path": $path, "type": $type, "summary": $summary}]' \
specs/state.json > specs/tmp/state.json && mv specs/tmp/state.json specs/state.json
fi
```
**Update TODO.md**: Add research artifact link.
---
### Stage 8: Git Commit
Commit changes with session ID:
```bash
git add \
"specs/${padded_num}_${project_name}/reports/" \
"specs/${padded_num}_${project_name}/.return-meta.json" \
"specs/TODO.md" \
"specs/state.json"
git commit -m "task ${task_number}: complete research
Session: ${session_id}
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>"
```
---
### Stage 9: Return Brief Summary
Return a brief text summary (NOT JSON). Example:
```
Research completed for task {N}:
- Found {count} relevant Mathlib theorems
- Identified proof strategy: {strategy}
- Created report at specs/{N}_{SLUG}/reports/MM_{short-slug}.md
- Status updated to [RESEARCHED]
- Changes committed
```
---
## Error Handling
### Input Validation Errors
Return immediately with error message if task not found.
### Metadata File Missing
If subagent didn't write metadata file:
1. Keep status as "researching"
2. Report error to user
### Git Commit Failure
Non-blocking: Log failure but continue with success response.
### Subagent Timeout
Return partial status if subagent times out (default 3600s).
Keep status as "researching" for resume.
---
## Return Format
This skill returns a **brief text summary** (NOT JSON). The JSON metadata is written to the file and processed internally.Related Skills
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