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list_entities

Retrieve active entities and concepts mapped in the personal knowledge network.

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_entities"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of entities to return (default 25).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden and does not meet it. The word 'active' hints that inactive/archived entities are excluded, which is genuinely useful, but nothing is said about ordering, pagination beyond the limit param, permissions/scopes, or whether the result is shallow or includes relationships.

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?

A single tight sentence with no filler, and the resource scope is front-loaded immediately. It loses a point only because a lone sentence cannot front-load usage or behavioral cues that would help an agent disambiguate.

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

Completeness3/5

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

This is a low-complexity read tool with zero required params, one fully documented parameter, and no output schema, so the description need not explain return values. However, it is silent on how results relate to sibling graph/search tools, which is the main ambiguity an agent faces in this toolset.

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?

There is a single parameter, 'limit', and its schema description already covers default 25 and maximum count at 100% coverage. The description adds no complementary meaning such as what happens when omitted or whether results are ordered before truncation, so the 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 uses a concrete verb ('Retrieve') plus a specific resource ('active entities and concepts mapped in the personal knowledge network'), so the agent knows this returns knowledge-network entity nodes. It falls short of a 5 because it does not distinguish the tool from close siblings such as query_graph, get_neural_cluster, or search_memory_vault, which also surface vault/graph content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to choose this tool over alternatives like query_graph (graph traversal) or search_vault (keyword search). The only usage signal is the word 'active', which implies a filter scope but is not explained as a selection condition.

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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