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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

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.

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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.

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