Skip to main content
Glama

AINumbers Fintech Intelligence Suite

by co.ainumbers

Kernel VM

run_kernel_vm
Read-onlyIdempotent

Run a ChainGraph decision kernel's compute(policy_parameters) inside a sandboxed, deterministic, in-browser QuickJS-ng WebAssembly VM (ocg-deterministic-compute@2) and return its output_payload. Demo kernel set only -- for the full catalog, use the worker's compute kernels directly. Renders the interactive AINumbers tool as a widget; inputs are applied via the AIN Bridge and the tool runs client-side (zero PII, zero network).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNoMap of tool input element IDs to values (see manifest input_schema). Applied via AIN Bridge prefill.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
elapsed_msNo
output_payloadNo

Schema Changelog

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

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "elapsed_ms": {
+      "type": "number"
+    },
+    "output_payload": {
+      "type": "object"
+    }
+  },
+  "type": "object"
+}
  2. Added

TDQS

A4.4/5.0
Behavior5/5

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

The description adds significant context beyond annotations: sandboxed, deterministic, in-browser QuickJS-ng WebAssembly VM, client-side execution, zero PII, zero network, widget rendering. No contradictions with annotations.

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?

Three sentences, each conveying essential information: core function, limitation, and security/UI details. No wasted words.

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

Completeness4/5

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

Covers purpose, limitations, runtime environment, and security. Slight gap in not detailing how the kernel is selected or the output schema, but the latter is provided separately.

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?

With 100% schema coverage, baseline is 3. The description adds minimal extra meaning beyond the schema, only mentioning that inputs are applied via AIN Bridge prefill and referencing the manifest.

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 clearly states that the tool runs a ChainGraph decision kernel's compute inside a sandboxed VM and returns the output. It distinguishes itself from siblings like 'run_chain' and explicitly notes it is for demo kernels only.

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?

The description provides explicit guidance: for the full catalog, use the worker's compute kernels directly. It also implies safe usage (zero PII, zero network) but does not exhaustively list when not to use.

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

C2.9/5.0
Disambiguation1/5

With 698 tools covering overlapping regulatory and compliance domains, many tools have near-identical names and purposes (e.g., check_genius_reserve_disclosure vs check_genius_reserve_disclosure_conformance, multiple DORA incident classifiers, several AP2 mandate validators). The highly templated descriptions further reduce distinctiveness, making reliable tool selection by an agent effectively impossible.

Naming Consistency4/5

The overwhelming majority of tools follow a consistent snake_case verb_noun pattern (assess_*, build_*, compute_*, validate_*, verify_*). Minor deviations exist (camt053_parse, workbook_evaluate, ha_gate_status, sdjwt_issue, etc.), but they are a small fraction of the total and follow recognizable domain-prefix conventions.

Tool Count1/5

698 tools is an extreme oversizing for any server, far beyond the 50+ threshold for a low score. Even with dedicated search/discovery tools, this unwieldy surface guarantees cognitive overload, high misselection risk, and severe practical usability problems.

Completeness4/5

The suite covers an extraordinarily broad range of fintech/regulatory domains — capital adequacy, AML, payments, crypto, AI governance, trade finance, and many verification/recompute lifecycles. Obvious gaps are difficult to identify, though the set is not a coherent single lifecycle and some niche areas are inevitably absent.

Resources