mnemostack

mnemostack_feedback

Record explicit feedback signals to improve memory retrieval through Q-learning. Log clicked or other signals, optionally with query, reward, and source labels, to update retrieval weights.

Instructions

Record explicit feedback for stateful recall learning.

Use signal='clicked' to also record inhibition-of-return exposure. Pass retriever labels from mnemostack_search results as sources so Q-learning can update source weights.

Input Schema

TableJSON Schema

Name	Required	Description
`query`	No	Natural language question or keyword associated with the feedback
`hit_id`	Yes
`reward`	No
`signal`	Yes
`source`	No
`sources`	No
`query_type`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.4.3Jun 9, 2026
- addedInput schema / properties / query / description
```
Added value: +"Natural language question or keyword associated with the feedback"
```
First observedv0.4.1May 11, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations; description mentions recording and Q-learning update but omits side effects, permissions, or idempotency. Adequate but not thorough.

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?

Three concise sentences, front-loaded with purpose, no fluff. Each sentence adds value.

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?

Has output schema, so return values covered. Covers core usage with sibling integration, but could elaborate on parameter behavior.

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?

14% schema coverage; description adds meaning for signal and sources but leaves hit_id, query_type, reward, source unexplained. Partially compensates.

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?

Clear verb-resource pair 'Record explicit feedback' with specific use case for signal='clicked'. Distinct from siblings like search and answer.

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?

Provides guidance on when to use (feedback recording) and how to connect with mnemostack_search. Lacks explicit exclusions but context is sufficient.

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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