Skip to main content
Glama

AINumbers Fintech Intelligence Suite

by co.ainumbers

FSMA 204 Critical Tracking Event (CTE) Validator

validate_fsma204_cte
Read-onlyIdempotent

FSMA 204 Critical Tracking Event (CTE) Validator: OpenChainGraph compute node (compliance_mandate). 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: art-119-traceability-lot-code-linker. Open at: https://ainumbers.co/chaingraph/art-118-fsma204-cte-validator.html FV-status (published/proven/still-trusted for this spec): /fv-status/e5ebd9cab6d424d5a202b2144bf9dacc14abf4ed24f3f0ac3adbecdd87c14872.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.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cte_typeNo
ftl_foodNo
cte_validNo
missing_kdesNo

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": {
+    "cte_type": {
+      "type": "string"
+    },
+    "cte_valid": {
+      "type": "boolean"
+    },
+    "ftl_food": {
+      "type": "string"
+    },
+    "missing_kdes": {
+      "type": "array"
+    }
+  },
+  "type": "object"
+}
  2. Added

TDQS

A3.7/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent, non-destructive), the description discloses deterministic execution, transient non-retention of inputs, the requirement for synthetic/anonymised inputs, AP2 artifact export with execution_hash, browser delegation behavior for gpu:true and compute:'browser', and an offline-verifiable FV-status receipt. This is rich behavioral context that no annotation captures.

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 contains useful details, but it is structured as a dense paragraph with redundancy (e.g., 'OpenChainGraph compute node' appears twice consecutively) and buries the primary validation purpose under infrastructure details like Cloudflare Workers and FV-status URLs. It could be trimmed and front-loaded with the validation semantics.

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

Completeness3/5

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

The schema and annotations cover parameters, safety, and output shape, and the description adds compute/privacy/pipeline context. However, the actual FSMA 204 CTE validation rules and the expected keys of policy_parameters are left to an external manifest and linked page, so an agent cannot fully determine correct domain inputs from this definition alone.

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?

All four parameters are already documented in the input schema (100% coverage), so the baseline is 3. The description mostly reiterates compute-mode behavior rather than adding new parameter meaning; parent_hashes and parent_tool_ids semantics remain in the schema, and policy_parameters is deferred to an external manifest.

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 the tool as a 'FSMA 204 Critical Tracking Event (CTE) Validator' and an 'OpenChainGraph compute node (compliance_mandate)', clearly tying it to a specific regulation and artifact type, which distinguishes it from the many other validate_* siblings. However, it never explains what validation entails (which CTE fields or rules are checked), so the core behavior remains implicit.

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

Usage Guidelines3/5

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

The description gives execution context (compute modes, gpu behavior, 'Use synthetic or anonymised inputs only') and states that the output feeds 'art-119-traceability-lot-code-linker', implying its place in a pipeline. It does not name alternative tools or state explicit when-to-use/when-not-to-use conditions relative to other validators, so routing guidance is mostly inferred.

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