skill-logic-research
Research mathematical logic tasks using domain context and codebase exploration. Invoke for logic-language research involving modal logic, Kripke semantics, and related mathematical foundations.
Best use case
skill-logic-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Research mathematical logic tasks using domain context and codebase exploration. Invoke for logic-language research involving modal logic, Kripke semantics, and related mathematical foundations.
Teams using skill-logic-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-logic-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How skill-logic-research Compares
| Feature / Agent | skill-logic-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 mathematical logic tasks using domain context and codebase exploration. Invoke for logic-language research involving modal logic, Kripke semantics, and related mathematical foundations.
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.
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SKILL.md Source
# Logic Research Skill
Thin wrapper that delegates mathematical logic research to `logic-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.
## Context References
Reference (do not load eagerly):
- Path: `.claude/context/formats/return-metadata-file.md` - Metadata file schema
Note: This skill is a thin wrapper with internal postflight. Context is loaded by the delegated agent.
## Trigger Conditions
This skill activates when:
- Task language is "logic"
- Research involves modal logic, Kripke semantics, or general mathematical logic
- Domain context files are needed for mathematical foundations
---
## 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.
---
### Stage 3: Create Postflight Marker
Create the marker file to prevent premature termination.
---
### Stage 4: Prepare Delegation Context
Prepare delegation context for the subagent:
```json
{
"session_id": "sess_{timestamp}_{random}",
"delegation_depth": 1,
"delegation_path": ["orchestrator", "research", "skill-logic-research"],
"timeout": 3600,
"task_context": {
"task_number": N,
"task_name": "{project_name}",
"description": "{description}",
"language": "logic"
},
"focus_prompt": "{optional focus}",
"metadata_file_path": "specs/{NNN}_{SLUG}/.return-meta.json"
}
```
---
### Stage 5: Invoke Subagent
**CRITICAL**: You MUST use the **Task** tool to spawn the subagent.
**Required Tool Invocation**:
```
Tool: Task (NOT Skill)
Parameters:
- subagent_type: "logic-research-agent"
- prompt: [Include task_context, delegation_context, focus_prompt, metadata_file_path]
- description: "Execute logic research for task {N}"
```
**DO NOT** use `Skill(logic-research-agent)` - this will FAIL.
The subagent will:
- Load domain context files from `.claude/context/project/logic/`
- Search codebase for existing patterns
- Use Mathlib lookup tools (lean_leansearch, lean_loogle, lean_leanfinder, lean_local_search)
- Execute web research for mathematical logic literature
- Create research report in `specs/{NNN}_{SLUG}/reports/`
- Write metadata to `specs/{NNN}_{SLUG}/.return-meta.json`
- Return a brief text summary (NOT JSON)
---
### Stage 6: Parse Subagent Return (Read Metadata File)
After subagent returns, read the metadata file.
---
### Stage 7: Update Task Status (Postflight)
If status is "researched", update state.json and TODO.md.
---
### Stage 8: Link Artifacts
Add artifact to state.json with summary.
---
### Stage 9: Git Commit
Commit changes with session ID using targeted staging.
---
### Stage 10: Cleanup
Remove marker and metadata files.
---
### Stage 11: Return Brief Summary
Return a brief text summary (NOT JSON). Example:
```
Research completed for task {N}:
- Found existing patterns in source files
- Loaded domain context for modal logic and Kripke semantics
- Used Mathlib lookup tools to discover relevant theorems
- Created report at specs/{NNN}_{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. Do not cleanup postflight marker
3. 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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