skill-math-research
- Repo stars 435
- Author updated Live
- Author repo nvim
- Domain
- Other
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @benbrastmckie · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- Local-only
- Install commands
- 26 variants
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。
---
name: skill-math-research
description: Research mathematical tasks using domain context and codebase exploration. Invoke for math-langu…
category: other
runtime: no special runtime
---
# skill-math-research output preview
## PART A: Task fit
- Use case: Research mathematical tasks using domain context and codebase exploration. Invoke for math-language research involving algebra, lattice theory, order theory, topology, and category theory..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Context References / Trigger Conditions / Execution Flow” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Research mathematical tasks using domain context and codebase exploration. Invoke for math-language research involving algebra, lattice theory, order theory, topology, and category theory.”.
- **02** When the source has headings, the agent prioritizes “Context References / Trigger Conditions / Execution Flow” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “Context References / Trigger Conditions / Execution Flow”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: skill-math-research
description: Research mathematical tasks using domain context and codebase exploration. Invoke for math-langu…
category: other
source: benbrastmckie/nvim
---
# skill-math-research
## When to use
- Research mathematical tasks using domain context and codebase exploration. Invoke for math-language research involving…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Context References / Trigger Conditions / Execution Flow” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "skill-math-research" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Context References / Trigger Conditions / Execution Flow
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Math Research Skill
Thin wrapper that delegates mathematical research to math-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 "math"
- Research involves algebra, lattice theory, order theory, topology, or category theory
- 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
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-math-research"],
"timeout": 3600,
"task_context": {
"task_number": N,
"task_name": "{project_name}",
"description": "{description}",
"task_type": "math"
},
"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: "math-research-agent"
- prompt: [Include task_context, delegation_context, focus_prompt, metadata_file_path]
- description: "Execute math research for task {N}"
DO NOT use Skill(math-research-agent) - this will FAIL.
The subagent will:
- Load domain context files from
.claude/context/project/math/ - Search codebase for existing patterns
- Use Mathlib lookup tools
- Execute web research for mathematical 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 algebra/lattice theory
- 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".
Git Commit Failure
Non-blocking: Log failure but continue with success response.
Return Format
This skill returns a brief text summary (NOT JSON). The JSON metadata is written to the file and processed internally.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review