Ecosystem Standards Review Protocol

This skill details how to perform an audit on new or existing capabilities (Skills, Plugins, Workflows, Sub-Agents, and Hooks) against authoritative ecosystem specifications to ensure they are created, installed, and structured correctly.

Instructions

When invoked to review a codebase component or a planned extension:

1. Identify the Component Type: Determine if the subject is a Plugin boundary, an Agent Skill, an Antigravity Workflow/Rule, a Sub-Agent, or a Hook.
2. Recall the Specs: Before reviewing, read the relevant specification file found in the ecosystem-authoritative-sources skill library.
   • Path: plugins/agent-skill-open-specifications/skills/ecosystem-authoritative-sources/reference/*.md
3. Perform Rigorous Audit:
   • Structure: Does the directory schema match the standard? (e.g., .claude-plugin/plugin.json, my-skill/SKILL.md).
   • Content: Does the YAML frontmatter adhere precisely to rules (e.g. description length limits, lower-case hyphenated names). If generating commands intended for explicit exclusion from GitHub/Gemini, use the exclude-targets array flag as defined in the standards.
   • Progressive Disclosure: For Skills, is the SKILL.md file appropriately constrained (< 500 lines) with extraneous detail pushed to one-level deep reference files?
   • Multi-CLI Support: When integrating agent CLI plugins, support exists for claude-cli, gemini-cli, and copilot-cli. Plugins must reflect the native CLI syntax in their system files.
   • Anti-Patterns: Check for hardcoded credentials, Windows style paths (\), silent error punting, and missing namespaces on MCP tool calls.
   • Connector Abstraction: If the plugin uses MCP tools, does it include a CONNECTORS.md using the ~~category abstraction pattern instead of hardcoding specific tool names? This is required for portability.
   • Interaction Design Quality: For skills with user interaction, verify they use appropriate patterns:
     • Discovery phases use progressive questioning (broad → specific), not question walls
     • Decision points offer numbered option menus (3-7 items max)
     • Expensive operations have confirmation gates
     • Multi-step workflows include inline progress indicators
     • Skills end with next-action menus, not dead ends
     • Workflows taking long documents gracefully degrade using Document Format Agnosticism.
   • Dual-Mode Architecture: If the skill both creates new artifacts AND improves existing ones, verify it implements the Bootstrap + Iteration dual-mode pattern with separate sections and trigger phrases.
   • Output Templates: If the skill generates reports or artifacts, verify it either defines an output template or negotiates the format with the user.
   • Escalation and Safety: Workflows with external risk must explicitly implement Graduated Autonomy Routing and Escalation Trigger Taxonomies rather than blanket-stopping on all issues.
   • Source Transparency: Data synthesis output MUST conclude with explicit Sources Checked and Sources Unavailable blocks.
4. Produce Feedback: Provide explicit, granular feedback outlining exactly which ecosystem constraints were violated and concrete suggestions for fixing them. Ensure your feedback is actionable.