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skill-idea-miner

Data Community
Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network
Domain
Data
Compatible agents
  • Claude Code
  • Cursor
  • Cline
  • Codex
  • Windsurf
  • Gemini CLI
  • +20
Trust score
88 / 100 · community maintained
Author / version / license
@tradermonty · no license declared
Token usage
Lean
Setup complexity
Plug-and-play
External API key
Not required
Operating systems
Unspecified (assume cross-platform)
Runtime requirements
Python >=3.10
Permissions
  • Read-only
  • Write / modify
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。

Output preview skill-idea-miner.preview 
---
name: skill-idea-miner
description: Mine Claude Code session logs for skill idea candidates. Use when running the weekly skill gener…
category: data
runtime: Python
---

# skill-idea-miner output preview

## PART A: Task fit
- Use case: Mine Claude Code session logs for skill idea candidates. Use when running the weekly skill generation pipeline to extract, score, and backlog new skill ideas from recent coding sessions..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to Use / Prerequisites / Workflow” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Mine Claude Code session logs for skill idea candidates. Use when running the weekly skill generation pipeline to extract, score, and backlog new skill ideas from recent coding sessions.”.
- **02** When the source has headings, the agent prioritizes “When to Use / Prerequisites / Workflow” 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; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, write/modify files; 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.
Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

  • Core job: Mine Claude Code session logs for skill idea candidates. Use when running the weekly skill generation pipeline to extract, score…
  • Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
  • Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

  • Structure: The skill is organized around “When to Use”, “Prerequisites”, “Workflow”, “Quick Start”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
  • Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
  • Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

  • Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
  • Invocation: Name skill-idea-miner directly; if the source includes slash commands, start with the command and then add task context.
  • Validation: Start small and check whether the result follows “When to Use / Prerequisites / Workflow” before expanding.

Boundaries And Review

  • Dependencies: It usually needs no extra API key, so start with a small validation task.
  • Permissions: Declared permissions include read / write; ask the agent to state file, command, and rollback boundaries before acting.
  • Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Discussion

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