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submit_feedback

Send feedback, a bug report, or a feature request to the Klyf team. If the user reports a specific problem or makes a specific request, even in one line (like 'the audit crashed on my last video' or 'let me export my winners to a spreadsheet'), send it right away this turn with kind set to bug, feature, or general; you can still ask a follow-up after. Only when the complaint is too vague to categorize (like 'something is wrong' or 'Klyf doesn't work' with no specifics) ask one short follow-up to pin down what happened, then send. A bug report about a Klyf tool (like a crashed audit) is feedback to log here, not a request to run that tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNobug for a problem or something broken, feature for a request or suggestion, general for other feedbackgeneral
messageYesA clear, specific description of the bug, feature request, or feedback

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false (a write) while destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuine behavioral value: it's a fire-and-forget logging action ('send it right away this turn, you can ask a follow-up after') and routes reports away from tool execution. It omits auth/rate-limit details, hence not a 5.

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?

Front-loads the purpose, then the when-to-use rules. Four sentences are justified by genuinely useful routing detail, though the phrasing around the follow-up and the final tool-vs-feedback clarification is slightly repetitive.

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 two-parameter, no-output-schema feedback tool, the description covers purpose, timing, categorization, and the tricky boundary with actionable tool requests. An agent has everything needed to call it correctly.

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?

Schema description coverage is 100%, including an inline description for the kind enum, so the schema already carries the parameter semantics. The description reinforces the categorization with concrete examples ('audit crashed'=bug, 'export my winners'=feature), which is mild added value but stays at the baseline.

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?

States a specific verb (Send) and resource (feedback/bug report/feature request) directed at a named recipient (the Klyf team). It also distinguishes itself from sibling action tools by clarifying that a bug report about a Klyf tool is feedback to log here, not a request to run that tool.

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

Usage Guidelines5/5

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

Explicitly defines when to send immediately (any specific problem or request, even one line) versus when to ask a follow-up first (only when the complaint is too vague to categorize). It gives concrete examples for both branches and clears up the boundary with tool-running siblings.

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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