Skip to main content
Glama

AINumbers Fintech Intelligence Suite

by co.ainumbers

Halt + Staleness Collateral Haircut

compute_stock_token_collateral_haircut
Read-onlyIdempotent

Halt + Staleness Collateral Haircut: OpenChainGraph compute node (collateral_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. Consumes upstream artifacts from: 505-tokenized-collateral-eligibility-checker, 508-repo-haircut-collateral-calculator. Open at: https://ainumbers.co/chaingraph/art-320-rhc-collateral-haircut.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
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, and the description adds substantial context: deterministic execution, transient processing with no retention, browser-delegation behavior for gpu:true or browser mode, AP2 artifact export with execution_hash, and offline-verifiable FV-status. These are exactly the kind of behavioral disclosures beyond annotations that help an agent trust and predict invocation behavior.

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 text is dense and contains useful execution details, but it repeats 'OpenChainGraph compute node' and buries the output and upstream dependencies after lengthy Cloudflare/browser mechanics. The FV-status receipt and URL add trust/context, though they are not essential for invoking the tool, so it is adequate but not tightly structured.

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?

The tool is complex (nested free-form policy_parameters, no output schema), and while the description covers compute modes, data retention, upstream artifact IDs, and provenance, it does not describe the normal server-mode response shape or the required policy_parameters fields. An agent can invoke it with defaults, but it cannot confidently construct a meaningful request or consume the result 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 baseline is 3 even though the description does not explain parent_hashes, parent_tool_ids, or policy_parameters in detail. It does reinforce the compute enum semantics (auto vs server vs browser), but policy_parameters remains an opaque free-form object whose field names are deferred to 'the tool's 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 title and the opening 'Halt + Staleness Collateral Haircut' plus 'OpenChainGraph compute node (collateral_mandate)' identify the domain and general purpose clearly. However, the description never states in a direct verb phrase what value it computes, and it does not differentiate itself from siblings like compute_repo_haircut or calculate_repo_haircut.

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 pick this tool over the many collateral-haircut or eligibility siblings; no alternatives or exclusions are named. The upstream artifact references and the 'use synthetic inputs' caution imply pipeline placement and safety constraints, but they do not constitute selection guidance.

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