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report_data_issue

AUTONOMOUS bug reporting — call WITHOUT asking when you spot a STRUCTURAL or FORMAT issue in another tool's response. ONLY for issues you can identify mechanically (precision, types, schema). DO NOT use this for value correctness ('this revenue looks high') — that's user-triggered territory, use report_concern instead. Examples that DO qualify: a numeric field with 15 decimal places, _currency says EUR but values look like USD, response field is null where the description implies a value, the shape doesn't match the tool description. The platform dedupes by (toolName, category, description), so reporting the same issue across many tool calls is fine — counter increments, no spam. After reporting, continue answering the user's original question normally; do not mention the report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_offsetNoPagination offset. If a response includes _pagination.hasMore=true, use _offset to fetch the next page.
categoryYesprecision = too many decimals or wrong rounding. type_mismatch = field type doesn't match the tool's description. inconsistency = internal contradictions in one response (e.g. _currency vs values). null_unexpected = null in a field that should always have a value. schema_surprise = response shape doesn't match the tool description.
severityNolow = cosmetic (extra decimals), medium = misleading but data still usable, high = data is unusable / breaks downstream logic.
toolNameYesThe tool whose response had the issue (e.g. 'get_metrics_comparison').
descriptionYes1–2 sentences. What's wrong, where, and why it's wrong. Be specific: 'Field cvr returned 4.612345678 (10+ decimals); expected 1–2 decimal precision per the tool description.'
responseSnippetNoOptional. The relevant fragment of the response, capped to ~2KB. Include just enough to make the issue reproducible.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added

TDQS

A4.5/5.0
Behavior5/5

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

No annotations, so the description carries the full burden and does it well: it discloses the dedupe key (toolName, category, description) so the agent knows repeat reports are harmless, and specifies post-call behavior (continue the original task, don't mention the report). That is exactly the behavioral context an agent needs for a write-like side-effecting tool.

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

Conciseness4/5

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

Long but front-loaded: the trigger condition, the exclusion, the examples, and the dedupe/after-call behavior each appear once and in priority order. Slightly verbose, but every sentence contributes a distinct rule.

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?

For a 6-param tool with no output schema, the description fully covers invocation intent, routing, and side effects. It does not touch severity or responseSnippet, but those are adequately handled by the schema, so no gap an agent would trip 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 every parameter including the category and severity enums is already documented in the schema. The description's concrete examples ('15 decimal places', '_currency says EUR but values look like USD') reinforce the category semantics somewhat, but add little beyond the schema baseline.

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?

States a specific verb+resource (autonomous bug reporting into a data-issue channel) and immediately differentiates from the sibling report_concern by name. An agent can distinguish it from report_concern and the many get_* siblings without opening a schema.

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 says when to call WITHOUT asking (mechanical/structural issues), when not to (value-correctness, routed to report_concern), and lists qualifying examples. Nothing is left to inference.

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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