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Meta-framework for discovering, installing, and integrating reusable AI agents. Provides tools to search and access AI agents with standard controller interface, HTTP/REST export, MCP support, and custom actions.
Single tool 'invoke' has critical definition gaps. Description is minimal (18 chars, below 20-char threshold). Input schema exists but is generic and underdescribed: 'input_data' parameter lacks any meaningful description beyond 'Input data'. No output schema documented. Tool name 'invoke' is generic and violates verb_noun pattern, does not convey what action occurs. No error handling guidance, no parameter constraints, no examples of expected input structure. Fails baseline: 100% of A+ tools have documented return types; 100% of A+ tool params have descriptions.
Invoke the agent
Tool name 'invoke' is generic and does not follow verb_noun pattern. LLMs cannot infer intent from the name alone. Should be renamed to reflect the actual agent action (e.g., 'run_agent', 'execute_agent', 'invoke_agent_task').
Tool description is 18 characters ('Invoke the agent'), below 20-char minimum and provides no context for LLM selection. Must explain WHAT the tool does, WHEN to use it, and WHAT it returns. Expand to 50 - 200 characters with actionable guidance.
Input parameter 'input_data' has no description. LLMs cannot determine what structure, fields, or values are expected. Must document: expected object shape, required/optional fields, constraints, and examples of valid input.
No output schema documented. LLMs need to know what fields and types the tool returns to plan downstream calls and extract data. Must define return structure (e.g., {result: string, status: string, metadata: object}).
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 30 | 2026-07-28+ | v2 |
No error handling guidance. Tool provides no recovery hints if invocation fails. Must categorize errors (retryable, user-fixable, fatal) and include actionable messages (e.g., 'Agent timed out. Retry with a shorter input or check agent logs.').