LQF_Machine_Learning_E…
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine…
Ensure thorough validation, error recovery, and transparent reasoning in research tasks with multiple tool calls
Claude Code
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill comprehensive-research-agent --agent claude-code
Codex
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill comprehensive-research-agent -a codex -y
Cursor
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill comprehensive-research-agent -a cursor -y
Gemini CLI
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill comprehensive-research-agent -a gemini-cli -y
GitHub Copilot
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill comprehensive-research-agent -a github-copilot -y
OpenCode
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill comprehensive-research-agent -a opencode -y
Windsurf
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill comprehensive-research-agent -a windsurf -y
name: comprehensive-research-agent description: "Ensure thorough validation, error recovery, and transparent reasoning in research tasks with multiple tool calls"
This skill addresses common failures in multi-step research tasks: unhandled tool errors, missing validation, opaque reasoning, and premature conclusions. It provides structured protocols for source validation, error recovery, and thinking transparency that significantly improves research quality and reliability.
1. After each tool call, explicitly check for errors in the response and acknowledge failures in the next thinking block with recovery strategy 2. Before reading URLs, rank sources by relevance/credibility and document selection rationale - never read results without evaluation 3. Thinking blocks must be 3-5+ sentences minimum and include: what was learned, connections to goal, gaps/contradictions, and next steps 4. Create a pre-completion checklist verifying: all requirements covered, sources retrieved, claims validated, gaps documented 5. Maintain source tracking - only cite URLs that were successfully fetched; prohibit citing unretrieved sources 6. When writing final reports, include 'Limitations & Gaps' section documenting what was attempted but failed or what remains unverified 7. Use read_file (not list_directory) to verify file content after save operations 8. Cross-validate key claims across at least 2 sources when possible; explicitly note consensus or contradictions 9. Track ga
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LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine…
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