Skip to main content
Glama

AINumbers Fintech Intelligence Suite

by co.ainumbers

GENIUS Act Monthly Reserve Disclosure Checker

check_genius_reserve_disclosure
Read-onlyIdempotent

GENIUS Act Monthly Reserve Disclosure Checker: OpenChainGraph compute node (compliance_mandate). Regulatory deadline: 2027-01-18 (GENIUS Act effective ≤ January 2027; monthly reserve composition reports required for licensed issuers; >$50B issuers subject to annual PCAOB audit. Re-verify against final-rule text on/after 2026-07-18.). Deterministic OpenChainGraph compute node. By default (compute:"auto") inputs are computed server-side on Cloudflare Workers for gpu:false nodes with a registered kernel; compute:"browser" forces client-side execution and returns a browser delegation URL instead. gpu:true nodes always delegate to the browser. Inputs are processed transiently to compute the response and are not stored, logged, or retained. Use synthetic or anonymised inputs only. Exports an AP2 artifact with execution_hash for chain provenance. Output feeds: ptg-01-ap2-prompt-template-generator. Open at: https://ainumbers.co/chaingraph/art-275-genius-reserve-disclosure-checker.html FV-status (published/proven/still-trusted for this spec): /fv-status/8b5ae30d812cd234cfb6068c4ce2022f01d10f2a358979b0f0d73421e09d2543.json — a snapshot, not a subscription; this receipt verifies offline regardless of whether that file is ever fetched.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
computeNoCompute mode (v0.4 Compute Binding). "auto" (default) = server for gpu:false nodes with registered kernels; "server" = force server-side; "browser" = always return browser delegation URL. gpu:true nodes always delegate.
parent_hashesNoexecution_hash values from upstream ChainGraph AP2 artifacts to chain from (sets chain.parent_hashes in the export).
parent_tool_idsNotool_id values matching parent_hashes, in the same order.
policy_parametersNoInput parameters for this tool's decision function. For gpu:false nodes with a registered kernel, these are computed server-side when compute is "auto" or "server". See the tool's manifest for field names.

TDQS

B3.1/5.0
Behavior4/5

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

The description adds meaningful behavioral detail beyond the readOnly/idempotent annotations: it is deterministic, inputs are processed transiently and not stored/logged/retained, and compute modes (auto/server/browser) are explained. This is useful context that helps an agent understand side effects and execution behavior.

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

Conciseness2/5

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

The description is dense and unstructured, mixing regulatory dates, provenance hashes, URLs, compute-mode behavior, output feeds, and FV-status in a single run-on block. It redundantly repeats 'OpenChainGraph compute node' and buries the most agent-relevant behavioral notes in a wall of parentheticals.

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

Completeness2/5

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

There is no output schema, and the description never explains what the tool returns: a boolean, a report, an artifact, or something else. The policy_parameters are left to a manifest, and the actual meaning of a 'reserve disclosure check' is not clarified. This is a significant gap for an agent trying to invoke the tool correctly and interpret its result.

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 schema already documents all four parameters. The description does not add field-level meaning beyond what is in the schema, and policy_parameters are explicitly deferred to a manifest. This meets the baseline but does not compensate for the opaque decision-function inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a specific resource and function: checking GENIUS Act monthly reserve disclosure. The title and opening line make the domain and subject clear, and the regulatory deadline provides context. However, it does not distinguish this tool from the sibling check_genius_reserve_disclosure_conformance, which appears to overlap heavily, and it never states the actual check outcome.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as check_genius_reserve_disclosure_conformance or check_mica_reserve_disclosure. The description gives regulatory context and advises using synthetic/anonymised inputs, but it does not explain the conditions that should lead an agent to select this tool.

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

All AINumbers Fintech Intelligence Suite 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

C2.4/5.0
Disambiguation1/5

Nearly every tool is an 'OpenChainGraph compute node' with identical boilerplate, and dozens of assess/check/validate/verify/lint/recompute verbs overlap heavily in purpose. An agent cannot reliably tell which of many similarly scoped tools should handle a given compliance or analytics question.

Naming Consistency2/5

Most names are snake_case, so there is superficial consistency, but the verb vocabulary is enormous and unpredictable, mixing build/compute/check/validate/verify/lint/assess/classify/score/reconcile and more. Several noun-first names such as pain001_validate, recon_match, and ha_record_validate further break the pattern.

Tool Count1/5

695 tools is far beyond any practical agent-facing surface, exceeding even the extreme end of the calibration range. This is a full product catalog dumped into one MCP server rather than a curated, usable tool set.

Completeness3/5

The suite covers an extremely wide range of fintech and regulatory calculators, validators, chain tools, and discovery utilities, so coverage is broad rather than thin. However, the lack of a clear domain boundary makes completeness nearly impossible to assess, and the heavy overlap suggests the surface was generated rather than intentionally designed.

Resources