get_proof
Verification proof: claim gates, or per-project proof links when a slug is given. Unknown slugs return an error.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No |
Verification proof: claim gates, or per-project proof links when a slug is given. Unknown slugs return an error.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose one real behavioral trait beyond the schema: unknown slugs return an error. It says nothing about read-only nature, auth/permission requirements, or rate limits, which for a proof/verification lookup are plausible concerns.
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 compact sentences, front-loaded with the resource and the mode switch. Nothing is padded, though the second sentence is a terse error note rather than substantive detail.
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, no-output-schema lookup this is nearly adequate: both modes and the error case are covered. It still leaves "claim gates" undefined and does not clarify what shape the proof data takes, which is the main thing an agent needs to use the result.
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?
Schema description coverage is 0% for the single slug parameter, so the description must compensate. It does explain the semantic effect of supplying slug (switches to per-project proof links), but gives no format, naming, or lookup rules for valid slugs.
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?
"Verification proof" names the resource and the two output modes (claim gates vs per-project proof links), but the verb is implied rather than stated and "claim gates" is unexplained jargon. An agent gets the gist but cannot confidently distinguish this from get_project or get_profile_summary without guessing.
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?
The description implies the usage rule — pass a slug for per-project proof links, omit it for claim gates — which is genuine conditional guidance. However, it names no alternatives and does not say when this tool should be preferred over its siblings.
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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