Read a temporary or pinned evidence snapshot by URI to verify a data answer, including exact query, frozen rows, source update time, completeness, methodology, and warnings.
Read a temporary or pinned evidence snapshot for verification. The snapshot contains the exact query, frozen rows, source update time, completeness, methodology, and warnings.
| Name | Required | Description | Default |
|---|---|---|---|
| snapshot_uri | Yes | The snapshot URI that query_dataset returned. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does useful work by enumerating the snapshot payload (query, frozen rows, source update time, completeness, methodology, warnings) and hinting at a temporary-vs-pinned lifecycle, but it says nothing about what happens with an expired or invalid URI, permission requirements, or failure modes — significant gaps for a read tool whose only parameter is a URI that can go stale.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with zero waste: the action and scope come first, then the payload contents. Every clause carries information an agent can use.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read tool with no annotations and no output schema, the description does the essential job of describing what comes back. The remaining hole is behavioral — nothing about expiry, errors, or access requirements for temporary snapshots, which is the main risk an agent needs to know about.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There is a single parameter with 100% schema description coverage, and the schema already explains that the URI is the one returned by query_dataset. The description adds no further syntax, format, or validation detail, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description pairs a specific verb (Read) with a specific resource (temporary or pinned evidence snapshot) and states its purpose (for verification). It is clearly distinct from siblings like pin_snapshot and query_dataset, though it doesn't name those alternatives explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: 'for verification' suggests reading back evidence after a query, and the schema notes the URI comes from query_dataset, which establishes the workflow ordering. However, the description itself states no explicit when-to-use condition, no mention of expired/unknown URIs, and no routing away from siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.