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@ainize/mcp

@ainize/mcp

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by ainblockchain
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Knowledge detail

get_knowledge
Read-only

Retrieve full details for a knowledge ID—claims, verification score, lineage, required stack, and ownership—before quoting or live-testing.

Instructions

Everything about one knowledge: what it claims, who verified it and with what score, its family, the base stack it needs (requires[]), and whether this node already holds or bought it. Read this before quoting or live-testing. Free.

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": "get_knowledge"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesthe knowledge id, e.g. "krx-all-2761"
includeNoextra sections; each costs one more read. lineage and requires are always included.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds genuinely new operational context: the call is 'Free', requires[] is part of the payload, and extra sections add further read cost. It does not cover failure modes (e.g., unknown id), keeping it below 5.

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 purpose, then a compact enumeration of returned fields and a single routing instruction. The trailing 'Free.' is terse but purposeful. The mid-sentence list is dense but every item carries information.

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?

With no output schema, the description must and does summarize the return shape, including the always-present requires[] from the schema. Combined with the cost note and the pre-quoting guidance, an agent has enough to call it correctly; only error/edge behavior is absent.

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 coverage is 100%, so the id format and the include enum with per-section cost are already documented. The description only echoes that requires[] is part of the default payload, adding marginal semantics beyond the schema. Baseline 3 applies.

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 names the resource precisely ('one knowledge') and enumerates the returned payload: claims, verifier and score, family, required base stack, and possession/purchase status. An agent knows exactly what this returns. It does not explicitly contrast with search_knowledge or family_tree, so it stops short of a 5.

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?

'Read this before quoting or live-testing' gives an explicit prerequisite that routes the agent to call this ahead of the quote sibling. There is no when-not guidance or mention of search_knowledge as the alternative when the id is unknown, so it is clear context but not full exclusion logic.

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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