skill-logic-research
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- Author repo nvim
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 type 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.jsonfocus_prompt- Optional focus for research direction
# 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 $task_number not found"
fi
# Extract fields
task_type=$(echo "$task_data" | jq -r '.task_type // "general"')
status=$(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:
{
"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}",
"task_type": "logic"
},
"focus_prompt": "{optional focus}",
"metadata_file_path": "specs/{NNN}_{SLUG}/.return-meta.json"
}
Stage 5: Invoke Subagent
CRITICAL: You MUST use the Agent tool to spawn the subagent.
Required Tool Invocation:
Tool: Agent (NOT Skill, NOT Plan)
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 5b: Self-Execution Fallback
CRITICAL: If you performed the work above WITHOUT using the Agent tool (i.e., you read files,
wrote artifacts, or updated metadata directly instead of spawning a subagent), you MUST write a
.return-meta.json file now before proceeding to postflight. Use the schema from
return-metadata-file.md with status value "researched".
If you DID use the Agent tool, skip this stage -- the subagent already wrote the metadata.
Postflight (ALWAYS EXECUTE)
The following stages MUST execute after work is complete, whether the work was done by a subagent or inline (Stage 5b). Do NOT skip these stages for any reason.
Stage 6: Parse Subagent Return (Read Metadata File)
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. Update TODO.md per @.claude/context/patterns/artifact-linking-todo.md with field_name=**Research**, next_field=**Plan**.
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:
- Keep status as "researching"
- Do not cleanup postflight marker
- 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.
- Fluxly category
- Other
- Author-declared agents
- No explicit declaration found; this is not inferred or tested compatibility
- Static check
- 88 / 100 · heuristic scan, not runtime safety proof
- Author / version / license
- @benbrastmckie · no license declared
- Fluxly token estimate
- Lean
- Fluxly setup estimate
- Guided setup
- External API key
- No requirement detected
- Detected OS requirements
- Unspecified
- Runtime requirements
- Unspecified
- Detected file/system behavior
-
- Read-only
- Write / modify
- Shell exec
- Detected network behavior
- Local-only
- Install commands
- None (reference only)
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
The current SKILL.md does not define a fixed output example. 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.
This skill activates when: Task type is "logic" Research involves modal logic, Kripke semantics, or general mathematical logic
Execution Flow
Validate required inputs: tasknumber - Must be provided and exist in state.json focusprompt - Optional focus for research direction
Update task status to "researching" BEFORE invoking subagent.
Create the marker file to prevent premature termination.
# 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 type 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 $task_number not found"
fi
# Extract fields
task_type=$(echo "$task_data" | jq -r '.task_type // "general"')
status=$(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
{
… Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.
sections -> Context References → Trigger Conditions → Execution Flow → Stage 1: Input Validation → Stage 2: Preflight Status Update → Stage 3: Create Postflight Marker
terms -> IMPORTANT · CRITICAL · Agent · Required Tool Invocation · DO NOT · Research · Plan · brief text summary
files/cmd -> logic-research-agent · .claude/context/formats/return-metadata-file.md · tasknumber · focusprompt · Skill(logic-research-agent) · .claude/context/project/logic/ · specs/{NNN}{SLUG}/reports/ · specs/{NNN}{SLUG}/.return-meta.json
body sha256 -> 95aad5929e81
Decide Fit First
Design Intent
How To Use It
Boundaries And Review