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add_feedback

Capture feedback from task execution to improve future recommendations by logging successes, failures, and improvement insights.

Instructions

Add feedback/learning from task execution to improve future recommendations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoOptional tags for categorization
typeYesType of feedback
taskIdYesTask ID to associate feedback with
patternYesPattern used or identified for similarity matching
feedbackYesFeedback text describing what was learned
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits on its own. It only states that feedback is added without mentioning side effects, idempotency, whether existing feedback is overwritten, or any prerequisites like a valid taskId. Minimal behavioral detail.

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 one concise sentence, front-loaded with the action 'Add', and contains no filler or redundant information. It is highly efficient.

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

Completeness3/5

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

Given the tool is a simple add operation with a fully-described schema, the description is minimally adequate. However, it lacks usage guidelines and behavioral transparency, making it incomplete for an agent that has no annotations to rely on.

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%, so parameters are already fully described in the schema. The description adds no additional parameter-level meaning, which aligns with the baseline of 3.

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 function: 'Add feedback/learning from task execution' with a specific purpose 'to improve future recommendations'. The verb 'Add' and resource are specific, distinguishing it from other record_* tools like record_decision or record_code_change.

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

Usage Guidelines3/5

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

The description implies usage after task execution ('from task execution') but does not explicitly state when to use it over alternatives. It lacks guidance on when-not-to-use or comparisons to similar sibling tools, though the purpose is somewhat implied.

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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