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CECL Expected Credit Loss & Allowance Calculator

calculate_cecl_ecl_allowance
Read-onlyIdempotent

CECL Expected Credit Loss & Allowance Calculator: OpenChainGraph compute node (credit_assessment). 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. Open at: https://ainumbers.co/chaingraph/art-426-cecl-ecl-calculator.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

B3.4/5.0
Behavior4/5

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

The annotations already indicate readOnlyHint, idempotentHint, and non-destructive. The description adds significant transparency: it explains determinism, transient processing (inputs not stored/logged/retained), server-side vs browser delegation, and the export of an AP2 artifact with execution_hash. It also notes the security guidance for synthetic data. No contradiction 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.

Conciseness3/5

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

The description is quite long and dense, packing many operational details (compute modes, data handling, URLs, FV-status) into a single block. The first sentence is clear, but the overall length could be trimmed. It's not poorly structured, but it could be more concise.

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?

For a calculator with no output schema, the description covers key context: it explains the compute binding, transient data handling, chain provenance via execution_hash, and provides a link and FV-status. It doesn't enumerate the exact policy_parameters fields (deferring to manifest), but the schema handles that. The description is adequate for an agent 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 description coverage is 100%, so the schema already documents all parameters thoroughly, including the compute enum and policy_parameters. The description doesn't add detail about parameter values or meanings beyond what the schema provides, so it relies on the schema, which is appropriate. Baseline score of 3 is warranted.

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 clearly states this is a CECL Expected Credit Loss & Allowance Calculator, a deterministic OpenChainGraph compute node. It identifies the domain (credit assessment) and the specific financial computation. However, it doesn't explicitly state the output format beyond an AP2 artifact, and it doesn't differentiate from other similar calculators beyond the name.

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?

The description provides operational guidance on compute modes and data handling (e.g., 'Use synthetic or anonymised inputs only'), but it doesn't explicitly state when to use this tool versus alternative calculators. No alternatives are mentioned, and the context for choosing this over similar compute tools is absent.

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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