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create_feedback

Create feedback for a trace or request by providing a trace ID and value. The feedback is linked immediately and returns the created feedback IDs and status.

Instructions

Create feedback for a trace or request. Writes a new feedback record linked by trace_id, returns the created feedback IDs and status, and takes effect immediately; use update_feedback when correcting an existing record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trace_idYesThe trace ID to associate the feedback with. This links feedback to a specific request/generation.
valueYesFeedback value/rating. Common patterns: 1 for positive (thumbs up), 0 for negative (thumbs down), or use a scale like 1-5.
weightNoOptional weighting factor for the feedback. Use to give more importance to certain feedback.
metadataNoOptional custom metadata for categorization and analysis (e.g., feedback_source, category, user_segment).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether the tool call succeeded and returned structured data
dataNoStructured success payload when ok is true
errorNoStructured error payload when ok is false
Behavior4/5

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

Annotations indicate a write operation (readOnlyHint=false). Description adds that it takes effect immediately and returns created feedback IDs and status, providing concrete behavioral context beyond annotations.

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?

Two sentences: first covers purpose and key behavior, second gives usage guidelines. No superfluous words.

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?

With output schema present, description covers return values, effect (immediate), and association via trace_id. Adequately complete for the tool's complexity.

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?

Input schema has 100% description coverage. Description confirms linking by trace_id and returning IDs/status, but adds minimal extra parameter-level detail beyond schema.

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?

Clearly states the tool creates feedback for a trace/request, specifies the resource (new feedback record), and distinguishes from sibling `update_feedback` by noting when to use that instead.

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 states when to use (to create feedback) and when not to use (use update_feedback for corrections), providing direct guidance and an alternative.

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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