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get_request_logs

Retrieve recent incoming HTTP requests captured by a mock endpoint. Each log entry shows: request headers, body, query params, matched rule label, response status returned, and response time. Use this to: (1) debug why a rule did or didn't match, (2) inspect the actual request payload structure your service sends, (3) verify the correct rule scenario was triggered. The 'matchedRuleLabel' field tells you which rule fired for each request.

Input Schema

NameRequiredDescriptionDefault
sizeNoNumber of most-recent logs to retrieve (default: 10, max recommended: 50)
mockIdYesID of the mock API endpoint to retrieve logs for
statusNoOptional HTTP status code filter to find specific response logs
ruleLabelNoOptional matched rule label filter (use 'Fallback' to match fallback default response)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden and does solid work: it discloses the exact shape of each log entry and explains that 'matchedRuleLabel' identifies which rule fired — genuinely useful behavioral context for interpretation. It stops short of covering retention windows, ordering guarantees, or what happens when no logs exist.

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

Conciseness4/5

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

Front-loaded with the core action and return shape, then a numbered list of use cases. The final sentence about 'matchedRuleLabel' partially restates the field list already given, but the slight redundancy earns its place as an interpretation aid.

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?

No output schema exists, so the description correctly steps in to describe the returned record fields in detail. For a 4-parameter read tool with no annotations, that covers the essential gap; missing only edge-case behavior (empty log sets, retention limits, whether logging is always enabled).

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?

Schema description coverage is 100%, so size, mockId, status, and ruleLabel are all already documented in the schema. The description's mention of 'matchedRuleLabel' refers to a returned field, not the ruleLabel filter parameter, so it adds no supplementary meaning to any input. Baseline 3 is correct here.

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?

States a specific verb and resource: 'Retrieve recent incoming HTTP requests captured by a mock endpoint', and enumerates exactly what each entry contains (headers, body, query params, matched rule label, status, timing). The purpose is unmistakable, though it never explicitly distinguishes itself from closely-named siblings like debug_last_request or get_saved_requests.

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?

Provides three concrete usage scenarios: debugging rule matching, inspecting outbound payload structure, and verifying the correct rule scenario fired. Clear context for when to reach for it, but no exclusions or named alternatives (e.g., when to use debug_last_request or get_saved_requests instead).

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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