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Glama

share_finding

Destructive

Create a shareable finding record from a DataBazaar dataset analysis and get a share URL to send to your team; make it public to help others discover the dataset.

Instructions

Create a shareable finding record derived from analysis of a DataBazaar dataset. Returns a share_url the operator can send to their team. Public findings also help others discover the underlying dataset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
publicNoWhether to make the finding publicly discoverable (default true)
summaryYes1-3 sentence summary of what was discovered
dataset_idYesThe dataset used to generate this finding

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.1

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already flag destructiveHint=true, so the write nature is covered by structured data. The description usefully adds that it returns a share_url and that public findings help others discover the dataset (implying visibility side effects), but it does not address permissions or the destructive implications of the write.

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?

Three short sentences, front-loaded with the core action and resource, then the return value and a secondary benefit. Efficient with little waste, though the third sentence is the most skippable.

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 3-parameter mutation tool with no output schema, the description covers the action, the return value (share_url), and the visibility consequence of going public. Only prerequisite/permission context is missing, keeping it shy of full 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 coverage is 100%, so the schema already documents public, summary, and dataset_id. The mention that 'public findings also help others discover the underlying dataset' loosely reinforces the public parameter but adds no format or syntax details beyond the schema, matching the baseline 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?

States a specific verb (Create) and a precise resource (shareable finding record derived from a DataBazaar dataset). No sibling tool produces findings, so there is no ambiguity to resolve, and the object acted upon is unambiguous.

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 phrase 'derived from analysis of a DataBazaar dataset' implies context of use, but the description never states when to call this versus alternatives or any prerequisites (e.g., must the dataset be analyzed first?). Usage is only implied, not spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.