Skip to main content
Glama

Council of AI GSPC

by io.github.CSOAI-ORG

rwa_evidence

PAID (x402). Per-request signed evidence card of ONE XRPL issued asset's deterministic on-ledger state via https://councilof.ai/api/rwa/evidence: AccountRoot lsf* flags, Domain, the two-way xrp-ledger.toml check (PASS / FAIL / UNCHECKABLE — unreachable is never FAIL), gateway_balances obligation, holders as the free reader has them, every raw fetch sha256'd. preview=true is free (unsigned state). Historical state at fetched_at — not a rating, not a guarantee, not a conformity mark; /api/xrpl and /root.json stay free. Without x_payment the tool returns the 402 challenge. If the route is not deployed on this origin the tool says NOT_DEPLOYED.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetYesSymbol (as listed by https://councilof.ai/api/xrpl) or issuer r-address.
previewNotrue = free unsigned state.
x_paymentNoThe X-PAYMENT header value signed 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

A4.4/5.0
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 payment flow, signed/unsigned states, hashing of fetches, deterministic snapshots at fetched_at, the three-way toml check behavior, and the NOT_DEPLOYED edge case.

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?

Information is front-loaded with the PAID qualifier and core purpose, and every sentence contributes meaningful detail. However, the content is packed into dense run-on sentences that could be easier to scan with structured bullets.

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?

Adequately complete for a complex paid tool with no output schema: it names the endpoint, the returned state components, free alternatives, payment behavior, preview behavior, and edge-case outputs. An agent has what it needs to call it correctly.

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 asset, preview, and x_payment. The description mostly restates these semantics rather than adding new parameter-level detail, though it does reinforce the payment challenge flow.

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 exactly what the tool produces: a per-request signed evidence card of one XRPL asset's deterministic on-ledger state, and names the concrete endpoint. The emphasis on evidence of state versus verification/inclusion makes it distinguishable from sibling tools like verify_card and verify_inclusion.

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?

Provides clear operational guidance: preview=true is free, omitting x_payment triggers the 402 challenge, and the tool is explicitly not a rating, guarantee, or conformity mark. It does not name sibling alternatives explicitly, but the paid/evidence-card context strongly implies when this tool applies.

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