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.
What this skill does
# 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 ```text ╔══════════════════════════════════════╗ ║ 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.
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.