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Abs Loan Level

by io.github.pipeworx-io
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Abs Trust Performance

abs_trust_performance
Read-onlyIdempotent

Delinquency-bucket performance history for ONE named securitization trust over its most recent N reporting months — loan count, balance, weighted-average APR and FICO per bucket (current / 1-29 / 30-59 / 60-89 / 90+ days past due / repossessed / charged-off). Use for "how is Ally Auto Receivables Trust 2024-2 performing?" or to track one deal's delinquency trend month over month. Get the exact trust name from abs_trusts first.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "trust": "CarMax Auto Owner Trust 2024-4  (CIK 0002037519)",
      "months": 6
    },
    "name": "abs_trust_performance"
  }
}

Input Schema

NameRequiredDescriptionDefault
trustYesExact trust display name, e.g. "Ally Auto Receivables Trust 2024-2". Case-sensitive exact match — look it up via abs_trusts if unsure.
monthsNoNumber of most-recent reporting months to return. Default 12, max 36.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, so the description is free to focus elsewhere and does: it enumerates the returned bucket taxonomy (current through charged-off) and the per-bucket metrics, which tells the agent what the payload looks like. It still omits any note on data recency, cost, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

Front-loaded with the deliverable, followed by the metric breakdown and then usage examples; every sentence carries information. The long parenthetical bucket list is dense but is the substantive content, not padding.

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?

With no output schema, the description usefully enumerates the returned fields and buckets, and the schema caps months at 36. Minor gaps: nothing about response volume for large N, result ordering, or behavior when the trust name doesn't match.

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 both parameters (trust, months) are already documented in the schema, including the default 12 and max 36. The description adds only the reminder that the trust name must come from abs_trusts, which the schema also repeats — baseline 3 applies.

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?

Specific verb+resource: delinquency-bucket performance history for ONE named securitization trust, with the exact granularity (loan count, balance, WA APR, FICO per bucket) spelled out. The 'ONE named trust' scope cleanly separates it from the portfolio-level abs_sector_delinquency and the lookup-only abs_trusts.

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?

Gives a concrete usage scenario ('how is Ally Auto Receivables Trust 2024-2 performing?') and a month-over-month trend use case, plus an explicit prerequisite routing step ('Get the exact trust name from abs_trusts first'). It never names when to prefer the sibling abs_sector_delinquency instead, so no exclusions or alternatives are stated.

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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