KyteApp

COMPLIANCE_CHECK

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# Install this skill:
npx skills add KyteApp/growth-agents-and-skills --skill "COMPLIANCE_CHECK"

Install specific skill from multi-skill repository

# Description

Apply the OpenAI SDK compliance checklist to audit files or directories and produce a Markdown report with findings and suggested fixes. Use when asked to "check compliance", "run compliance check", or "audit against OpenAI SDK rules".

# SKILL.md


name: COMPLIANCE_CHECK
description: Apply the OpenAI SDK compliance checklist to audit files or directories and produce a Markdown report with findings and suggested fixes. Use when asked to "check compliance", "run compliance check", or "audit against OpenAI SDK rules".


COMPLIANCE CHECK

Owner: QA

Goal

Audit a target (file set or directory) against .claude/checklists/openai-sdk-compliance-checklist.yaml and deliver a Markdown report with evidence and actionable fixes.

Workflow

1. Load Inputs

  • Read target_path (file, directory, or list).
  • Respect context: apply strictly to agent implementations, tools, and orchestration code.

2. Evaluate Rules

  • Process rules top-down (A1 → A11).
  • Apply activation_hint and stop_condition:
  • Stop on first HIGH unless --exhaustive is requested.
  • Stop if findings_count > 25.

  • Enforce Kira Constitution and OpenAI Agents SDK standards:

  • A1. Primitives Only: Orchestration uses only run()/Runner.run() and handoff(); no extra verbs like routeAgent or pipeTo.
  • A2. Tool Categories Valid: Every tool is one of: Function | Hosted | Agent-as-Tool | MCP.
  • A3. No Custom Routing: No bespoke agent-to-agent communication (axios/fetch/custom) beyond SDK patterns.
  • A4. Tool Input Schema (Zod): All tools define parameters via tool({ parameters: z.object({...}) }).
  • A5. Structured Outputs (Zod): Agents with non-text outputs declare outputType: z.object({...}).
  • A6. Single RunContext: One canonical RunContext<T> shared across agents/tools/guardrails.
  • A7. History Threading: Conversation history flows via result.history → next run().
  • A8. Model Settings Casing: Uses modelSettings.toolChoice (camelCase), not tool_choice.
  • A9. Tracing Enabled/Declared: Tracing wired to Langfuse (or explicitly disabled with rationale).
  • A10. Vision & Whisper Usage: Use OpenAI Vision for images/PDFs and Whisper for audio; custom file analysis only for text formats.
  • A11. Deterministic IDs via Context: IDs (userId, wid, aid, etc.) come from RunContext; never inferred or generated by agents.

  • For each rule:

  • Mark PASS/FAIL with evidence (file path + line/snippet).
  • For FAIL, provide a concrete fix that matches the rule’s fix guidance.
  • Preserve severity and autofix flags from the checklist.

3. Apply Lean Guards

  • Do not expand scope beyond meta.scope.
  • Prefer small, safe fixes.
  • Refactor only when required by a rule.
  • Skip large migrations.
  • If a standard conflicts with a functional requirement, flag it for manual review rather than forcing a breaking change.

4. Produce Report

  • Follow the checklist output_schema.
  • Include:
  • Summary: counts by severity + decision (READY | NEEDS_REVISION | BLOCKED).
  • Findings: list items with id, severity, file, symbol (if known), evidence, fix, autofix.
  • Suggestions: targeted next steps based on findings.

5. Save Output

  • Write Markdown to docs/qa/reports/compliance-{{target_slug}}.md.
  • Create directories if missing.

Anti-Patterns

  • Do not mark PASS without evidence.
  • Do not invent IDs, symbols, or file paths.
  • Do not ignore severity: HIGH violations.
  • Do not propose custom orchestration verbs or "clever" routing logic that bypasses the SDK.
  • Do not recommend using raw tool_choice or messages arrays without SDK types.
  • Do not allow UUID generation inside agents (must come from context).

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.