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Kingfisher Streaming Inference

Kingfisher Streaming Inference

by J-X0
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

verify_audit

Recompute and validate the full audit hash chain to confirm the integrity of every logged decision in the streaming inference trail.

Instructions

Recompute and verify the entire audit hash chain.

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": "verify_audit"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals only the action ('recompute and verify') but not whether the operation mutates state, what side effects might occur, how expensive it might be, or what failure behavior looks like. This is a significant gap for a tool that likely performs a substantial computation.

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?

One precise sentence with no filler. The verb and target are front-loaded, and every word contributes to understanding the tool's purpose. This is appropriately concise for a no-parameter tool.

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

Completeness2/5

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

The description lacks information about the outcome of the verification: what does it return, does it throw on failure, does it produce a report, and is it a read-only check or a recomputing mutation? With no output schema and no annotations, the agent is left without enough context to confidently use the tool and interpret results.

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?

The tool has zero parameters, so there is no schema information to supplement. The baseline for 0 parameters is a 4, and the description correctly avoids inventing parameters. It does not need to explain parameter semantics because none exist.

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 states a specific verb ('Recompute and verify') and a specific resource ('the entire audit hash chain'), making the tool's function unambiguous. It is clearly distinct from the sibling tools ingest_event, stream_stats, and export_audit, which handle ingestion, statistics, and export respectively.

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 use case is implied: if you want to verify the audit hash chain, this is the tool. However, there is no explicit guidance about when to prefer it over alternatives, nor any exclusions or prerequisites.

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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