Skip to main content
Glama

Council of AI GSPC

by io.github.CSOAI-ORG

commission_card

PAID (x402). Commission one signed card-v0 receipt (surface ras.commission) for a named subject on the frozen bank via https://councilof.ai/api/request-attestation. Re-serves every signed measurement card already on file for the subject; a payment never mints a MEASURED cell (fresh_run stays UNMEASURED until a published run exists). Without x_payment the tool returns the 402 challenge (accepts[] with asset, amount, payTo) plus a free preview of the cards already on file. Measurement, not certification — never a rank, a grade or a certificate. Verification stays free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
axisNoOptional axis slug; omit for the subject-level commission.
subjectYesSubject to commission: a model id, instrument id or card sha (1-120 chars of [A-Za-z0-9._:/@+-]).
x_paymentNoThe X-PAYMENT header value (base64 x402 payload) signed by your wallet against accepts[] from the previous 402. Omit to receive the challenge.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly: it discloses the paid nature, conditional 402/challenge response, resurfacing of existing measurement cards, and the guarantee that payment never mints a MEASURED cell. This goes well beyond the basic mutating behavior implied by 'commission'.

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

Conciseness5/5

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

The description is dense but efficient, leading with the most important fact (PAID x402) and then covering purpose, conditional behavior, exclusions, and verification in a few sentences. Every sentence carries information needed to invoke the tool correctly.

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 paid, no-output-schema tool, the description supplies the full call pattern: omit x_payment to receive the 402 challenge, and include it to commission. It also clarifies edge-case semantics around fresh_run and measurement, leaving no critical gap for an agent to guess.

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 the baseline of 3 applies; the schema already documents subject, axis, and x_payment. The description adds behavioral context about challenge retrieval and preview, but does not add meaningful parameter-level semantics beyond what the input schema states.

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?

The description names a specific verb and resource: commission one signed card-v0 receipt for a subject via a specific endpoint. It also explicitly distinguishes itself from certification and verification, so an agent can tell it apart from sibling tools like verify_card.

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?

It clearly explains the x402 payment flow, including what happens when x_payment is omitted, and states exclusions ('never a rank, a grade or a certificate') and that verification stays free. It does not name a specific sibling tool to switch to, but the context is clear enough for tool selection.

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

All Council of AI GSPC toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Each tool has a distinct target resource or action, but some boundaries require careful reading: get_card, verify_card, and verify_inclusion all deal with cards/proofs, while art50_marking_evidence and rwa_evidence are both paid evidence packs. The detailed descriptions help separate them, so misselection is unlikely but not impossible.

Naming Consistency3/5

There are clear verb-prefixed clusters like get_axis/get_card/get_root and verify_card/verify_inclusion, but several tools use bare noun phrases: board_totals, commission_card, receipts_batch, rwa_evidence, and art50_marking_evidence. The naming is readable and snake_case throughout, but the verb/noun convention is mixed.

Tool Count5/5

With 11 tools, the set is well-scoped for a GSPC board, measurement-card, evidence, and verification server. Each tool serves a distinct endpoint or workflow, and none feels redundant or purely decorative.

Completeness4/5

The surface covers board totals, axis details, roots, card retrieval, verification, paid evidence, and historical receipts. A minor gap is the absence of a list_axes tool to enumerate all board axes or a direct get_measurement_card endpoint, but existing tools can work around this via list_cards and verify_card.

Resources