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RiskPilot

RiskPilot

by dushaorighthere
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

riskpilot_audit

Read-onlyIdempotent

Read and verify local hash-linked audit events. Access paper-fill records to confirm data integrity and trace trade decisions.

Instructions

Read and verify all local hash-linked audit events. Contains paper data only.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "riskpilot_audit"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

The annotations already declare read-only, idempotent, and non-destructive behavior, so the description does not need to restate those. It adds useful context about the data being 'local hash-linked' and 'paper data only', but the meaning of 'paper data' is unclear, and it does not disclose anything about verification semantics or output behavior. This is adequate but not rich.

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 two short sentences with no filler. The core action and resource are front-loaded in the first sentence, and the second sentence adds a meaningful scope qualifier. Every word earns its place, apart from minor ambiguity in 'paper data'.

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?

For a parameterless, read-only tool with supportive annotations, the description is largely complete: it states what the tool operates on and its scope. The lack of an output schema means return values are not specified, but the simplicity of the tool and the strong annotations reduce the need for that detail. The main gap is the undefined 'paper data' term and lack of guidance on output shape.

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?

There are zero parameters and schema description coverage is 100% vacuously, so the description has no burden to explain parameter details. The baseline of 4 applies here because there is nothing parameter-related that needs clarification.

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 uses the specific verb phrase 'Read and verify' with a clear resource, 'all local hash-linked audit events', which distinguishes it from the sibling tools dealing with policy and analysis. The scope is well-defined, though the phrase 'Contains paper data only' is ambiguous and may confuse an agent about what 'paper data' refers to.

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 gives clear context that this tool is for reading and verifying local hash-linked audit events, which makes its intended use apparent relative to the sibling tools. It does not explicitly state when not to use it or name alternatives, but the domain is specific enough that an agent can infer appropriate usage.

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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