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classdesk

by de.classdesk
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Wunschbox-Nachrichten als gelesen markieren

mark_feedback_read

Markiert Einträge (ids aus list_feedback) als gelesen – z. B. nachdem du sie zusammengefasst hast.

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": {
      "ids": "<ids>"
    },
    "name": "mark_feedback_read"
  }
}

Input Schema

NameRequiredDescriptionDefault
idsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

The annotations already establish that this is a non-read-only but non-destructive, closed-world operation. The description adds the specific effect of marking entries as read, but does not cover idempotency, error behavior, permissions, or what exactly changes in the system.

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 a single compact sentence with the action front-loaded, followed by the parameter source and a practical example. It contains no redundant wording.

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 one-parameter mutation with annotations covering safety hints and no output schema, the description provides enough context to call the tool correctly. It could say more about the result of marking as read, but that is a minor gap.

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 carry parameter meaning. It identifies the sole parameter as IDs from list_feedback, which is useful semantic context beyond the raw array-of-strings schema, though it does not discuss format or constraints.

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: entries are marked as read. It also clarifies that the IDs come from list_feedback, which helps distinguish this tool from unrelated siblings, though it does not explicitly contrast with other mutation tools.

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?

It gives a clear use case: use this after summarizing entries. The dependency on list_feedback is implied for obtaining IDs, but there are no explicit exclusions or alternatives described.

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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