AgentSkillsCN

backend-diagnose-workflow

在Claude中,无需调查员/验证者/求解子智能体,即可开展后端诊断工作流。通过自信控制,完成证据收集、验证与解决方案推导。

SKILL.md
--- frontmatter
name: backend-diagnose-workflow
description: Backend diagnosis workflow for Claude without investigator/verifier/solver subagents. Performs evidence collection, validation, and solution derivation with confidence control.

Backend Diagnose Workflow

Purpose

  • Execute /diagnose-equivalent flow in a single agent.
  • Produce root-cause-oriented recommendations with explicit confidence.

Workflow

  1. Structure problem type:
    • change failure
    • new discovery
  2. Collect missing context and constraints.
  3. Gather evidence: logs, traces, failing tests, reproduction steps.
  4. Build hypotheses and causal chains.
  5. Validate hypotheses with minimal reproducible checks.
  6. Derive solution options with tradeoffs.
  7. Choose recommendation and define implementation steps.
  8. Record residual risks and post-fix verification items.

Confidence Policy

  • high: enough evidence to implement recommended fix safely.
  • medium: additional investigation likely required but bounded.
  • low: fundamental evidence gaps remain.

If confidence is below high, iterate investigation up to two additional loops. After two loops, escalate decision to user.

Required Output Structure

  • identified causes
  • cause relationships (independent/dependent/exclusive)
  • investigated scope
  • recommendation with rationale
  • alternatives
  • residual risks
  • post-resolution verification checklist

Hard Rules

  • Do not stop at symptom-level conclusions.
  • Do not skip alternative-hypothesis evaluation.
  • Do not propose fixes without impact and regression analysis.