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Mnemento

Mnemento

by reddol18
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_schemas

Retrieve schema definitions and record types, including fields, allowed values, drafts, and organize approval history, to inspect how structured facts are validated and stored.

Instructions

Record types with their fields, descriptions and allowed values, plus drafts (unregistered fields and values already in use) and the history of organize approvals.

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_schemas"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses non-obvious content traits (unregistered fields/values already in use, approval history), but it says nothing about read-only nature, scope, filtering behavior, pagination, or permissions.

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 dense sentence with no filler, front-loaded on the primary content (record types and fields). It is slightly run-on when enumerating drafts and approval history, but nothing is wasted.

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?

Because an output schema exists, return values need not be spelled out, yet the description reasonably previews the payload shape. However, for a tool whose only input is undocumented, the definition is not complete enough to call confidently without opening the schema.

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 single parameter 'name' has 0% schema description coverage and is never mentioned in the description, so its purpose (presumably filtering by record type) is unexplained. The description does not compensate for the coverage gap, leaving the only input ambiguous.

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 a specific resource — record types (schemas) — and enumerates what comes back: fields, descriptions, allowed values, drafts, and organize-approval history. An agent can tell this is a read of schema definitions, but it never states an explicit verb and offers no differentiation from nearby tools like propose_schema or apply_schema_proposal.

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 call this versus alternatives such as propose_schema, apply_schema_proposal, or query. The description only characterizes the payload, leaving the agent to infer that this is the inspection counterpart to the proposal tools.

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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