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Hybrid

verify_mock

Read-onlyIdempotent

Validate that a mock API endpoint received the expected number of calls, with optional constraints for minimum or maximum invocations.

Instructions

Check whether a mock was called the expected number of times. Returns pass/fail status, actual call count, and invocation details. Optionally assert with expected_count, at_least, or at_most parameters. Use this to assert your application is making the right API calls.

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": {
      "id": "<id>"
    },
    "name": "verify_mock"
  }
}

Input Schema

NameRequiredDescriptionDefault
at_leastNoMinimum invocations expected
at_mostNoMaximum invocations expected
expected_countNoExpected number of invocations (exact match)
idYesMock ID to verify

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations indicate read-only and idempotent operations, which the description aligns with by describing a checking/assertion function. The description adds valuable behavioral context: it specifies the return format ('pass/fail status, actual call count, and invocation details') and explains the optional assertion parameters ('at_least, or at_most'), which are not covered by annotations.

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 front-loaded with the core purpose in the first sentence, followed by return details and usage guidance. Each sentence adds value: the first defines the tool, the second specifies outputs, and the third provides context. There is no wasted text.

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 (verification with optional parameters), annotations cover safety (read-only, idempotent), and the description explains purpose, returns, and usage. However, there is no output schema, so the description partially compensates by mentioning return details, but it could be more explicit about output structure (e.g., format of 'invocation details').

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

Parameters3/5

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

The input schema has 100% description coverage, so the schema already documents all parameters well. The description adds minimal semantics by mentioning 'Optionally assert with expected_count, at_least, or at_most parameters,' which reinforces but does not significantly expand beyond the schema. This meets the baseline for high schema coverage.

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: 'Check whether a mock was called the expected number of times.' It specifies the verb ('Check'), resource ('mock'), and scope ('expected number of times'), distinguishing it from sibling tools like 'get_mock_invocations' (which likely lists calls) or 'reset_verification' (which resets counts).

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

Usage Guidelines4/5

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

The description provides clear usage context: 'Use this to assert your application is making the right API calls.' It implies this tool is for verification/assertion purposes, but it does not explicitly state when not to use it or name alternatives (e.g., 'get_mock_invocations' for non-assertive checking).

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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