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Roastify Check Proof Status

roastify_check_proof_status

Check whether a proof grant is still valid.

Mirrors check_oauth_status for the npub-proof flow: a calling agent can ask "will my next paid call accept this dpop_token?" before burning credits on a guaranteed failure. Expiry is read from the grant itself; the only store consulted is the patron's revocation watermark.

Free, no side effects — touches no relay.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dpop_tokenNoRequired. The grant envelope returned by ``receive_npub_proof``.
patron_npubNoRequired. The patron's npub (npub1...).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / dpop_token / description
      Previous value: -"Required. The dpop_token phrase returned by\n``request_npub_proof`` / ``receive_npub_proof``."New value: +"Required. The grant envelope returned by\n``receive_npub_proof``."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does so well: 'Free, no side effects — touches no relay', plus 'expiry is read from the grant itself; the only store consulted is the patron's revocation watermark.' That tells the agent this is a non-mutating local read with a bounded data source. It does not mention auth requirements or failure behavior, which keeps it at 4.

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?

Front-loaded with the purpose, then rationale, then behavioral facts — every sentence earns its place. The middle sentence is somewhat long and ornate ('a calling agent can ask...'), a minor drag on conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter read tool this covers purpose, motivation, side-effect profile and data sources. An output schema exists, so return values need not be explained, and nothing an agent needs to invoke it correctly is missing.

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?

Schema coverage is 100%, so baseline is 3. The description adds real meaning by mapping each parameter to its role: the grant (dpop_token) supplies expiry, the patron_npub is consulted only for the revocation watermark. That is semantic value beyond the schema's type/default declarations.

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 and resource ('check whether a proof grant is still valid') and frames the concrete question it answers ('will my next paid call accept this dpop_token?'). This distinguishes it from the request/receive npub-proof siblings, which mint or transport grants rather than validate them.

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?

Gives a clear when-to-use trigger: run it before a paid call to avoid 'burning credits on a guaranteed failure'. It also names its analogue (check_oauth_status) and, via the schema, the tool that produced the token. No explicit when-not or exclusions are stated, so it stops short of a 5.

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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