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report_feedback

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Report data quality issues or agent intent gaps to improve accuracy and relevance of DataNexus tool responses.

Instructions

Report a data quality issue or agent intent gap for a DataNexus tool response.

tool_id: e.g. "T10" or "security_fetch_cve_detail". query_hash: From the query_hash field of the response. signal: incorrect_data | missing_field | stale_data | not_useful | wrong_entity | data_quality. comment: Issue description. Max 500 chars. missing_fields: Absent or wrong field names. feedback_type: "user_feedback" (default) or "agent_gap". intended_query: Agent's goal. Max 256 chars. gap_description: What was missing. Max 256 chars.

Example: report_feedback(tool_id="T10", query_hash="abc123", signal="incorrect_data")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tool_idYesTool identifier, e.g. T04 or security_fetch_cve_detail. Required.
query_hashYesHash from the response being reported — found in the query_hash field of any response. Required.
signalYesOne of incorrect_data, missing_field, stale_data, not_useful, wrong_entity, or data_quality. Required for user_feedback.
commentNoDescription of the issue. Optional. Max 500 characters.
missing_fieldsNoList of field names that are absent or wrong. Optional.
feedback_typeNouser_feedback (default) or agent_gap. Use agent_gap when the tool returned a valid response but did not serve the user's actual need.user_feedback
intended_queryNoWhat the agent was trying to accomplish — used when feedback_type=agent_gap. Optional. Max 256 chars.
gap_descriptionNoWhat was missing or wrong in the result — used when feedback_type=agent_gap. Optional. Max 256 chars.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior1/5

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

The description states the tool creates a report (a write operation), but annotations declare `readOnlyHint: true`, which implies no side effects. This is a direct contradiction. The description also does not clarify behavioral traits like side effects, data persistence, or response expectations beyond the contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is informative but somewhat verbose. It includes parameter descriptions in a list format and an example, which helps structure. However, it could be more concise, as some points are redundant with the schema.

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?

Given the tool has 8 parameters, 3 required, and an output schema, the description covers basic usage but lacks important context due to the annotation contradiction. It does not explain return values or confirm whether the tool is idempotent, leaving gaps in completeness.

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 the description adds some value by providing an example and clarifying the use of `feedback_type` and `agent_gap`. However, it largely reiterates schema details without significant new meaning. Baseline is 3, and this meets it.

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 purpose: 'Report a data quality issue or agent intent gap for a DataNexus tool response.' It uses specific verbs and resources, and it distinguishes from sibling tools that perform other functions like data retrieval or API management.

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?

The description provides a concrete example (`report_feedback(tool_id="T10", query_hash="abc123", signal="incorrect_data")`) that guides usage. It explains required and optional parameters, but does not explicitly state when not to use the tool or compare it to alternatives.

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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