agent4.io

get_knowledge_index

Show the structured index profile: per column coverage, type, numeric range, top values, warnings.

**The warnings are the point.** On a real 4,500-document catalogue this surfaced three data
problems nobody knew about: 1,058 documents with `page_count` 0, 505 with `reading_level` 0,
493 with `word_count` 0 — those are not zeros, they are missing values recorded as 0, and they
silently poison every average, minimum and range filter built on them.

Report the warnings to the user in their own terms ("493 of your books have no word count —
they will all tie for shortest"). Nothing else in the platform will ever tell them.

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": {
      "name": "<name>"
    },
    "name": "get_knowledge_index"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedAug 4, 2026

TDQS

A4.1/5.0

Behavior5/5

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

With no annotations, the description carries full responsibility. It goes beyond a simple read operation by explaining that zeros are missing values that 'silently poison every average, minimum and range filter,' includes a real-world example, and instructs the agent on how to report findings. This is strong behavioral disclosure.

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 a clear summary, then a bolded emphasis and a detailed anecdote. The anecdote is compelling but adds length; still, each sentence earns its place by reinforcing the tool's value and usage guidance.

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?

The description covers purpose, behavioral nuances, and reporting expectations. With an output schema present, it doesn't need to describe return values. The main gap is parameter semantics, but overall this is a well-rounded description.

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

Parameters2/5

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

The schema has zero description coverage for the single 'name' parameter, and the description never clarifies that 'name' refers to the knowledge index being inspected. While the parameter is named intuitively, the description provides no additional meaning, leaving the agent to infer what name is expected.

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 opens with a specific verb+resource: 'Show the structured index profile' and lists concrete components (coverage, type, numeric range, top values, warnings). This clearly distinguishes it from sibling tools like build_knowledge_index and patch_knowledge_index, which modify rather than read the index.

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 frames the warnings as the tool's central purpose and notes 'Nothing else in the platform will ever tell them,' implying this is the go-to tool for surfacing data-quality issues. However, it does not explicitly name alternatives or state when not to use it, so it's clear but not fully explicit.

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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