Static source inference · medium confidence · detected: Logging
Deprecated protocol patterns detected
Summary
Three tools with action verbs and present input schemas, but significant quality gaps. Tool descriptions are adequate (120-145 chars, within baseline range), but parameter descriptions are sparse or missing. describe_image_url and describe_image_file have identical structures with minimal differentiation. The detail_level parameter lacks an enum constraint despite having known valid values ('basic', 'detailed', 'comprehensive'). Output schema is undocumented, responses are JSON strings rather than structured objects. No error recovery guidance provided. No tool annotations (readOnly, destructive, idempotent). Overall parameter quality is mediocre: 2 of 3 tools document only 2 params when they should document functional constraints.
detail_level parameter lacks enum constraint. Values 'basic', 'detailed', 'comprehensive' are documented only in the description text, inviting hallucinated values from the LLM. Should declare as enum in schema.
Output schema is completely undocumented. Tools return JSON-wrapped strings (e.g. '{"description": ..., "metadata": ...}') but agents cannot parse the structure without explicit schema documentation. LLMs must reverse-engineer the response format.
Duplicate tool responsibilities. describe_image_url and describe_image_file are near-identical in structure and behavior (both accept detail_level, both call Grok API for analysis). Agents cannot easily distinguish when to use which. Should consolidate with a single 'analyze_image' tool accepting either url or file_path parameter.
describe_image_urldescribe_image_file
Recommendations
Add enum constraint to detail_level parameter: {"enum": ["basic", "detailed", "comprehensive"]} in the JSON Schema. Remove example values from description text.
Consolidate describe_image_url and describe_image_file into a single 'analyze_image' tool with parameters: source (union of url|file_path, document mutually exclusive relationship), detail_level (enum), format (optional, enum: ['json', 'text']). This reduces cognitive load and eliminates duplicated logic.
Add file-based variant to extract_text_from_image. Rename to 'extract_text' and accept either url or file_path (document mutual exclusivity). Return structured {text: string, source: string, image_metadata: {format, size}} instead of wrapped JSON string.
Add error recovery guidance. If GROK_API_KEY is missing, return: 'GROK_API_KEY environment variable not set. Set it in your environment and retry, or contact your administrator for API access.' Distinguish retryable errors (timeout, rate limit) from permanent errors (invalid key, unsupported format).
Declare tool annotations in FastMCP. Add readOnlyHint=true to all tools (they do not modify state). Add idempotentHint=true to all tools (repeated calls with same input produce same output).
Spec posture evidence
Inferred effective spec: <=2025-11-25.
Relies on Logging (deprecated) - log to stderr or use OpenTelemetry
extract_text_from_image accepts only URL input, not local files. Symmetric with describe_image_file which accepts local files. Creates inconsistent API surface, agents cannot extract text from local files, forcing extra workflow steps.
No error recovery guidance. Errors are returned as emoji-prefixed strings ('❌ API Error: ...') but provide no actionable next steps. If GROK_API_KEY is missing, the agent learns the key is missing but not how to proceed or recover.
No tool annotations. None of the tools declare readOnlyHint, and no tools are marked idempotent. Agents cannot determine if repeated calls are safe or if they have side effects.
Required parameter validation is weak. url and file_path accept empty strings but validation happens inside the tool handler, not in schema constraints. Should enforce minLength:1 and appropriate format patterns in JSON Schema.
Add minLength and format constraints to schema. For url parameters: format='uri'. For file_path parameters: minLength=1, pattern='^[./].*\.(jpg|jpeg|png|gif|webp|tiff|bmp)$' (case-insensitive).
Return structured objects instead of JSON-wrapped strings. Use FastMCP's typed return annotations to define output schema formally. Example: @mcp.tool() async def describe_image_url(...) -> dict: {"description": str, "metadata": {...}, ...}
Add timeout parameter to HTTP calls (already present at 30s for image fetch, 60s for API, but document in tool description: 'Analysis may take up to 60 seconds.'). Add explicit guidance if timeout occurs.
Remove emoji prefixes from error messages. Replace '❌ Error: ...' with structured error: {"error": "<error_type>", "message": "<user_facing_message>", "recovery": "<action_suggestion>"}.