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report_feedback

Submit feedback about incorrect, outdated, or incomplete data from any DataNexus tool response. Specify the tool, query hash, and issue type to help improve data quality.

Instructions

Report a data quality issue with any DataNexus tool response. Call this after receiving a result that appears wrong, outdated, or incomplete — for example: an EIN returns the wrong organisation, a CVE severity looks incorrect, or a field expected in the response is absent. Parameters: tool_id (required) — 'T04' (nonprofit) or 'T10' (vulnerability), the tool that returned the suspect result. query_hash (required) — the query_hash field from that tool response. signal (required) — one of: incorrect_data, missing_field, stale_data, not_useful, wrong_entity. comment (optional) — description of what appears wrong (max 200 chars). Returns: {'status': 'recorded'} — always. Response time: <200 ms. No auth required. Token-efficient.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tool_idYes
query_hashYes
signalYes
commentNo
missing_fieldsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, description carries full burden and fully discloses behavior: returns fixed dict, response time <200 ms, no auth required, token-efficient. No side effects disclosed, but mutation minimal. No contradiction with annotations (none).

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?

Very concise yet comprehensive. Two short paragraphs with bullet-style parameter list. Every sentence adds value. No unnecessary 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?

Given the simple nature of the tool and presence of output schema, description covers most aspects: purpose, when to use, parameters, and return format. Missing only description of missing_fields parameter. Overall adequate.

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

Parameters4/5

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

Description explains all required parameters (tool_id with valid values, query_hash, signal with enum list, comment with max length) and adds meaning beyond schema. However, does not describe missing_fields parameter present in schema (coverage 0%), which is a gap.

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's purpose: report data quality issues with DataNexus tool responses. Uses specific verb 'report' and resource, with concrete examples (EIN, CVE). Distinguishes from siblings as the only feedback/reporting tool, though does not explicitly differentiate from validate_tool_output.

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 clear guidance on when to call the tool ('after receiving a result that appears wrong, outdated, or incomplete') with specific examples. Lacks explicit when-not-to-use or alternatives, and does not mention sibling validate_tool_output, but usage context is well-defined.

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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