| name | ecosystem-standards |
| description | Provides active execution protocols to rigorously audit how code, directory structures, and agent actions comply with the authoritative ecosystem specs. Trigger when validating new skills, plugins, or workflows. |
| disable-model-invocation | false |
| allowed-tools | Bash, Read, Write |
| dependencies | ["skill:ecosystem-authoritative-sources"] |
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:
- 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.
- Recall the Specs: Before reviewing, read the relevant specification file found in the
ecosystem-authoritative-sources skill library.
- Path:
../../references/*.md
- Perform Rigorous Audit:
- Structure: Does the directory schema match the standard (
.claude-plugin/plugin.json, my-skill/SKILL.md)? Are all supporting files strictly organized into the official optional directories (scripts/, references/, assets/) rather than cluttering the skill root?
- Naming: Verify the skill name uses the gerund form (
verb + -ing, e.g., analyzing-spreadsheets). Reject generic nouns. Ensure the name is 1-64 lowercase alphanumeric chars/hyphens only, contains NO consecutive hyphens (--), and EXACTLY matches the parent directory name.
- Content: Does the YAML frontmatter adhere precisely to rules (
description 1-1024 chars, compatibility max 500 chars, metadata strictly string-to-string keys/values)? Provide the recommendation to run skills-ref validate ./my-skill to definitively catch parse errors.
- Description Viewpoint: Ensure the
description is written strictly in the third person ("Extracts text", not "I extract text") and isn't overly vague.
- Progressive Disclosure: For Skills, is the
SKILL.md file appropriately constrained (< 500 lines) with extraneous detail pushed to one-level deep reference files? Reject deeply nested reference chains.
- Reference Paths: Verify that all file references are strictly relative to the skill's root (e.g.,
scripts/extract.py), avoiding absolute paths outside the plugin boundaries.
- Reference Readability: Do reference files >100 lines contain a Table of Contents for partial-read navigation?
- Script Quality: Verify python utility scripts do not punt errors back to the LLM (e.g., failing silently), but instead handle exceptions safely or emit clear
stderr messages. Ensure they don't use undocumented "magic numbers" (voodoo constants).
- 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 and Windows style paths ().
- Produce Feedback: Provide explicit, granular feedback outlining exactly which ecosystem constraints were violated and concrete suggestions for fixing them. Ensure your feedback is actionable.
