ai-ml-api-automation

Automate AI ML API tasks via Rube MCP (Composio). Always search tools first for current schemas.

50.00x

Quality

46%

Does it follow best practices?

Impact

100%

50.00x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./composio-skills/ai-ml-api-automation/SKILL.md

Quality

Discovery

22%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This description is too vague to effectively guide skill selection. It fails to specify what concrete actions the skill performs, lacks natural trigger terms users would say, and provides no explicit 'Use when...' guidance. The only distinguishing element is the tool name 'Rube MCP (Composio)' which most users won't know to reference.

Suggestions

Add a 'Use when...' clause specifying trigger scenarios, e.g., 'Use when the user wants to integrate with AI/ML services like OpenAI, Hugging Face, or needs to orchestrate ML pipelines'

Replace 'Automate AI ML API tasks' with specific concrete actions, e.g., 'Call OpenAI endpoints, manage Hugging Face models, orchestrate ML inference pipelines'

Include natural user terms like 'GPT', 'language models', 'AI integrations', 'ML workflows' that users would actually say when needing this skill

Dimension	Reasoning	Score
Specificity	The description uses vague language like 'Automate AI ML API tasks' without listing any concrete actions. No specific capabilities are enumerated - what tasks? What APIs? What automation actions?	1 / 3
Completeness	The 'what' is extremely vague ('automate tasks') and there is no 'when' clause or explicit trigger guidance. The instruction to 'search tools first' is operational guidance, not a usage trigger.	1 / 3
Trigger Term Quality	Contains some relevant keywords ('AI', 'ML', 'API', 'Composio', 'Rube MCP') but these are technical jargon rather than natural user language. Missing common variations users might say like 'machine learning', 'artificial intelligence APIs', or specific service names.	2 / 3
Distinctiveness Conflict Risk	The mention of 'Rube MCP (Composio)' provides some distinctiveness, but 'AI ML API tasks' is broad enough to potentially conflict with other AI/ML related skills. The specific tool reference helps but the task scope is unclear.	2 / 3
	Total	6 / 12 Passed

Implementation

70%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill provides a solid structure for AI ML API automation with clear workflow sequencing and good validation checkpoints. The main weaknesses are moderate redundancy between sections and the use of pseudocode-style examples rather than fully executable code with realistic parameter values. The pitfalls section adds genuine value by addressing common failure modes.

Suggestions

Remove the standalone 'Tool Discovery' section since it duplicates Step 1 of the Core Workflow Pattern

Provide at least one complete, realistic example with actual tool slugs and arguments that would work for a common AI ML API task

Consolidate the session ID guidance - it's mentioned in multiple places with slightly different phrasing

Dimension	Reasoning	Score
Conciseness	The content is reasonably efficient but includes some redundancy - the 'Tool Discovery' section repeats information that appears again in 'Core Workflow Pattern Step 1', and some explanations could be tighter.	2 / 3
Actionability	Provides concrete tool call patterns with parameter examples, but uses pseudocode-style notation rather than actual executable code. The arguments shown are placeholders rather than real working examples.	2 / 3
Workflow Clarity	Clear 3-step workflow with explicit validation checkpoint (Step 2 checks connection status before execution). The 'Known Pitfalls' section provides good error prevention guidance and the sequence is unambiguous.	3 / 3
Progressive Disclosure	Well-structured with clear sections progressing from prerequisites to setup to workflow to pitfalls. External reference to toolkit docs is one level deep and clearly signaled. Quick reference table aids navigation.	3 / 3
	Total	10 / 12 Passed

Validation

90%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: ComposioHQ/awesome-claude-skills
Commit: 2790447

Reviewed: about 1 month ago

Table of Contents

Discovery Implementation Validation

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