preflight-mcp

report_outcome

Report API or MCP server call outcomes to contribute to community reliability ratings. Submit success, error, timeout, or unexpected results with latency and error details.

Instructions

Leave a review — report the outcome of an API or MCP server call you just made. Like writing a TrustPilot review, your report contributes to the community reliability rating for that service.

The more agents that report, the more accurate the ratings become for everyone.

Args: service: Service slug that was called outcome: Result — 'success', 'error', 'timeout', or 'unexpected' latency_ms: Response time in milliseconds (if available) error_type: If outcome was 'error', the category: 'auth', 'rate_limit', 'server', 'network', 'parse', 'other'

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "service": "<service>",
      "outcome": "<outcome>"
    },
    "name": "report_outcome"
  }
}

Input Schema

Name	Required	Description	Default
`service`	Yes
`outcome`	Yes
`latency_ms`	No
`error_type`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.10.0Mar 20, 2026

TDQS

A4.4/5.0

Behavior3/5

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

With no annotations provided, the description carries full burden. It explains the tool's purpose (reporting outcomes) and community impact, but doesn't disclose important behavioral traits like whether this is a read-only operation, if it requires authentication, rate limits, or what happens after submission. The description doesn't contradict annotations (none exist), but leaves significant behavioral aspects unspecified.

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?

The description is well-structured and appropriately sized. It starts with the core purpose, provides community context, then lists parameters with clear explanations. Every sentence earns its place: the first establishes purpose, the second explains value, and the parameter section provides necessary details without redundancy.

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

Completeness4/5

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

Given the tool's moderate complexity (4 parameters, 2 required) and the presence of an output schema (which means return values are documented elsewhere), the description is reasonably complete. It explains what the tool does, when to use it, and provides parameter semantics. The main gap is lack of behavioral transparency details (permissions, side effects, etc.), but with an output schema handling return values, it's mostly adequate.

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?

Schema description coverage is 0%, so the description must compensate. It provides clear semantic explanations for all 4 parameters: 'service' (Service slug that was called), 'outcome' (Result with specific values), 'latency_ms' (Response time in milliseconds), and 'error_type' (category if outcome was error). The description adds substantial meaning beyond the bare schema, though it doesn't explain the 'null' defaults for optional parameters.

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

Purpose5/5

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

The description clearly states the tool's purpose: 'Leave a review — report the outcome of an API or MCP server call you just made.' It uses specific verbs ('Leave a review', 'report the outcome') and identifies the resource (API/MCP server calls). It distinguishes from siblings by focusing on outcome reporting rather than checking or comparing reliability.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool: 'report the outcome of an API or MCP server call you just made.' It provides context about contributing to community reliability ratings. While it doesn't explicitly name sibling tools as alternatives, it clearly defines the specific use case (reporting outcomes after calls), which implicitly distinguishes it from checking or comparing reliability.

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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