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mnemostack_feedback

Record explicit feedback to improve stateful recall learning. Use signal='clicked' for inhibition-of-return and pass retriever labels as sources to update Q-learning 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
NameRequiredDescriptionDefault
hit_idYes
signalYes
queryNo
query_typeNo
sourceNo
sourcesNo
rewardNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the special behavior of signal='clicked' and the role of sources in weight updates, but lacks details on persistence, error handling, or response structure.

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 concise with three sentences, each adding value. It front-loads the core purpose and provides targeted usage tips without unnecessary fluff.

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

Completeness2/5

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

Despite having an output schema, the description does not explain the return value or fully describe the 7 parameters. The integration with search is hinted but not fully detailed, making completeness low for a complex tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description should compensate but only explains 'signal' and 'sources' partially. Five other parameters (hit_id, query, query_type, source, reward) have no description, leaving significant gaps.

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 records explicit feedback for stateful recall learning. It distinguishes from siblings (answer, health, search) by its feedback-specific focus and mentions advanced usage with Q-learning updates.

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 provides specific context for using signal='clicked' and passing sources from search results. While it doesn't explicitly state when not to use the tool or compare to alternatives, the context is sufficiently clear for a learning-oriented feedback tool.

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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