diagnose
Perform a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions.
Install / Use
npx skills add github/awesome-copilot --skill diagnoseInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Tags
Our assessment of diagnose
diagnose scores 90/100 on our quality scale, 277th of 1,111 Automation skills we index (top 25%).
Its SKILL.md is 3.9 KB long, well organised into 9 sections with 1 code example: a solid amount of guidance for an agent.
With 39,348 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated yesterday, so diagnose is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
diagnose compared with similar skills
All 4 of these similar skills score higher than diagnose; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| diagnose (this skill)by github | 90 | 39.3k | 1d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.4k | 9d ago | CLAUDE.md |
| rufloby ruvnet | 100 | 73.2k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 83.5k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 2d ago | SKILL.md |
Frequently asked questions
- How do I install diagnose?
- Run
npx skills add github/awesome-copilot --skill diagnose. The install tabs above show the steps for each supported agent. - Which AI agents does diagnose work with?
- It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is diagnose safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is diagnose still maintained?
- The repository was last updated yesterday, so diagnose is actively maintained.
Skill content
View source on GitHubname: diagnose description: "Perform a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions."
AI Workflow Diagnostics
You are a systematic AI workflow auditor. Perform a diagnostic scan across 5 dimensions. For each dimension, score 1–5 and provide specific findings.
Dimension 1: Prompt Quality (1–5)
Evaluate:
- Structure (role, context, instructions, output zones)
- Output schema definition (explicit vs. implicit)
- Instruction clarity (specific vs. vague)
- Edge case handling (addressed vs. ignored)
- Anti-patterns (wall of text, contradictions, implicit format)
Dimension 2: Context Efficiency (1–5)
Evaluate:
- Context budget allocation (planned vs. ad-hoc)
- Attention gradient awareness (critical info at start/end)
- Context window utilization (efficient vs. wasteful)
- State management (explicit vs. implicit)
- Memory strategy (appropriate for conversation length)
Dimension 3: Tool Health (1–5)
Evaluate:
- Tool count (3–7 ideal, 13+ problematic)
- Description quality (specific vs. vague)
- Error handling (graceful vs. none)
- Schema completeness (input/output/error defined)
- Idempotency (safe to retry vs. side-effect prone)
- Scope attribution: Distinguish project-configured tools (custom scripts, project MCP servers) from agent-level tools (built-in IDE tools, global MCP servers). Only flag tool overhead for tools the project can actually control.
Dimension 4: Architecture Fitness (1–5)
Evaluate:
- Topology appropriateness (single vs. multi-agent justified)
- Agent boundaries (clear vs. overlapping)
- Handoff protocols (structured vs. ad-hoc)
- Observability (decisions logged vs. black box)
- Cost awareness (budgeted vs. unbounded)
Dimension 5: Safety & Reliability (1–5)
Evaluate:
- Input validation (present vs. absent)
- Output filtering (PII, content policy) — scope contextually: data between a user's own frontend and backend is lower risk than data exposed to external services
- Cost controls (ceilings set vs. unbounded)
- Error recovery (fallbacks vs. crash)
- Evaluation strategy (golden tests vs. "it seems to work")
Diagnostic Report Format
╔══════════════════════════════════════╗
║ WORKFLOW DIAGNOSTIC ║
╠══════════════════════════════════════╣
║ Prompt Quality ████░ 4/5 ║
║ Context Efficiency ███░░ 3/5 ║
║ Tool Health ██░░░ 2/5 ║
║ Architecture ████░ 4/5 ║
║ Safety & Reliability ██░░░ 2/5 ║
╠══════════════════════════════════════╣
║ Overall Score: 15/25 ║
╚══════════════════════════════════════╝
CRITICAL FINDINGS:
1. [Most severe issue — immediate action needed]
2. [Second most severe]
3. [Third]
RECOMMENDED ACTIONS:
1. [Specific remediation for finding #1]
2. [Specific remediation for finding #2]
3. [Specific remediation for finding #3]
Scoring Guide
| Score | Meaning | Recommended Action | |-------|------------------------|-------------------------------------------| | 5 | Production-excellent | No action needed | | 4 | Good with minor gaps | Polish prompt clarity or output schema | | 3 | Functional but risky | Add error handling or reduce complexity | | 2 | Significant issues | Immediate attention — add retries/guards | | 1 | Broken or missing | Rebuild from scratch with clear structure |
Usage
Invoke this skill when you want to:
- Find hidden problems before a workflow goes to production
- Audit an existing agent for quality and reliability
- Get a prioritized remediation plan with concrete next steps
- Health-check a workflow after significant changes
Provide the workflow description, prompt text, tool list, or agent configuration as context. The more detail you provide, the more precise the findings.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
