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by com.petabloom
OverviewAdmin

Give Feedback

give_feedback

Send structured feedback about bugs, missing data, unclear behavior, or feature requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
feedbackYesFeedback for the server team. Include the problem, missing capability, or suggested improvement without sensitive user data.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYesFeedback persistence status.
messageYesHuman-readable result summary.
feedback_idYesStable feedback identifier.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • removedInput schema / properties / contact
      Removed value: -{
-  "default": "",
-  "description": "Optional follow-up contact details (e.g. email address, handle, or preferred channel) the server team can use if they address the feedback or have clarifying questions. Only provide with user consent; leave empty to remain anonymous.",
-  "maxLength": 500,
-  "type": "string"
-}
  2. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already indicate the tool is not read-only and may have external effects (openWorldHint=true). The description adds context about the feedback types but does not disclose what happens after sending (e.g., persistence, confirmation). No contradiction with annotations.

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?

A single sentence that front-loads the verb and resource, with no unnecessary words. Every phrase earns its place.

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

Completeness5/5

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

For a simple tool with one parameter and an output schema, the description is complete. It clearly sets expectations for what to send and what the tool is for. No additional behavioral details are required.

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?

The schema fully describes the single 'feedback' parameter (100% coverage). The tool description adds value by enumerating the feedback categories (bugs, missing data, unclear behavior, feature requests), which enriches understanding beyond the schema's basic 'problem, missing capability, or suggested improvement'.

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 clearly states the tool's action ('Send structured feedback') and its scope ('about bugs, missing data, unclear behavior, or feature requests'). This unambiguously distinguishes it from all siblings, which are retrieval/search operations.

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 implies usage for reporting issues or requests to the server team. It provides clear context but does not explicitly name alternatives or state when not to use the tool. However, sibling tools are all read/search operations, so no real ambiguity exists.

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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