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check_status

Track service request status using the request ID to monitor progress and view completion state.

Instructions

Check the status of a Soma request.

request_id: the ID returned by submit_request

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler function for the 'check_status' MCP tool. It takes a request_id, loads requests from storage, checks if the request exists, and returns formatted status information including the request status, text, quoted sats (if any), and contact information.
    @mcp.tool()
    def check_status(request_id: str) -> str:
        """Check the status of a Soma request.
    
        request_id: the ID returned by submit_request"""
        reqs = load_requests()
        if request_id not in reqs:
            return f"Request '{request_id}' not found."
        r = reqs[request_id]
        lines = [f"Request {request_id}: {r['status']}",
                 f"  {r['text']}"]
        if r.get("sats"):
            lines.append(f"  Quoted: {r['sats']} sats")
        if r.get("contact"):
            lines.append(f"  Contact: {r['contact']}")
        return "\n".join(lines)
  • server.py:181-181 (registration)
    The MCP tool registration decorator. The @mcp.tool() decorator registers the check_status function as an MCP tool named 'check_status' in the FastMCP server.
    @mcp.tool()
  • The input schema is defined through the function signature (request_id: str) and docstring. The docstring describes the parameter and serves as documentation for the LLM.
    def check_status(request_id: str) -> str:
        """Check the status of a Soma request.
    
        request_id: the ID returned by submit_request"""
  • Helper functions used by check_status. load_requests() reads the requests.json file and load_requests() saves data back. These are used to persist and retrieve request data.
    def load_requests():
        if REQUESTS_FILE.exists():
            return json.loads(REQUESTS_FILE.read_text())
        return {}
    
    def save_requests(data):
        REQUESTS_FILE.write_text(json.dumps(data, indent=2, ensure_ascii=False))
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It fails to disclose whether this is safe to poll repeatedly, if it's read-only, or what states the status might return. These are critical gaps for a status-checking tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero waste. The purpose is front-loaded ('Check the status...'), followed immediately by the parameter semantics. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a single-parameter tool with an output schema (so return values needn't be described), but clear gaps remain regarding behavioral traits (idempotency, polling safety) that are important for status-checking operations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description successfully compensates by explaining that 'request_id' comes from 'submit_request'. This provides crucial semantic context linking the parameter to the sibling tool's output, though it lacks format constraints or examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Check') and resource ('status of a Soma request'). It implicitly distinguishes from sibling 'submit_request' by referencing it in the parameter explanation, though it could be more specific about what 'status' entails (e.g., completion state vs health check).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The parameter description implies a workflow ('the ID returned by submit_request'), suggesting when to use this tool. However, it lacks explicit guidance on polling behavior, rate limits, or when NOT to use this versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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