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knowl_feedback

Record append-only usefulness feedback after a knowledge item is used, rejected, or causes a correction. This captures real-world relevance to improve future retrieval.

Instructions

Record append-only usefulness feedback only after a retrieved item was actually used, rejected, or caused a correction.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usedNoWhether the result was used.
itemIdYesKnowledge item ID.
usefulNoWhether the result was useful.
causedCorrectionNoWhether the result caused a correction.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv5.23.0

TDQS

A4.2/5.0
Behavior4/5

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

The description reveals the key behavioral trait that feedback is append-only, which is not visible from the annotations or schema. This adds meaningful transparency beyond the structured metadata, though it could go further in describing response behavior or effect on other entries.

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, tightly worded sentence that front-loads the core action ('Record append-only usefulness feedback') and immediately follows with the usage constraint. No filler or redundant phrasing exists.

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 boolean feedback tool with no output schema, the description covers the purpose, the mutation behavior, and the triggering condition. It could mention what happens if called with contradictory flags, but that is a minor gap given the schema's clarity.

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 coverage is 100%, so the baseline applies. The description does add a useful semantic tie between the boolean parameters and real-world conditions ('used, rejected, or caused a correction'), but it doesn't redefine or clarify individual parameters beyond what the schema already states.

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 uses a specific verb-resource pair, 'Record append-only usefulness feedback', and adds an explicit condition about when it is allowed. This clearly differentiates it from sibling tools like knowl_store or knowl_evidence_list without needing further context.

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?

'Only after a retrieved item was actually used, rejected, or caused a correction' provides a clear timing trigger for the tool. It doesn't name alternative tools, but the conditional guidance is strong enough to prevent premature or arbitrary calls.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.