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by LinkedParticles
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Python
Hybrid

list_corpus_entries

Retrieve recent corpus entries in most-recently-deposited order, with optional limits and source-type filters, so you can inspect stored claims and their origins.

Instructions

List recent corpus entries (most-recently-deposited first).

Args:
    limit: Maximum entries to return (default 50).
    source_type: Optional filter (e.g. ``"WIKIDATA_API"``).

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": "list_corpus_entries"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
source_typeNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.210.2

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It discloses the ordering and the limit default, which are useful, but it does not explicitly confirm read-only behavior, pagination semantics, permissions, or rate limits.

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 short and front-loaded: the core action and ordering appear first, followed by compact Args explanations. Every sentence adds useful information with no waste.

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 simple two-parameter list tool, the description covers the key call semantics, and the presence of an output schema means return values need not be explained. The main remaining gap is the absence of explicit read-only or permission context due to missing annotations.

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?

Schema description coverage is 0%, so the description must compensate. It documents both parameters: limit as maximum entries with default 50, and source_type as an optional filter with an example value, though it does not enumerate all valid source_type values.

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 states a specific verb and resource: "List recent corpus entries," and adds the ordering "most-recently-deposited first." This clearly distinguishes it from sibling tools that list other resources, though it does not explicitly name an alternative.

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 description implies usage by specifying recent entries and an optional source_type filter, but it does not say when to choose this tool over alternatives such as corpus_links_suggest or query. No explicit when-not or alternative guidance is provided.

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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