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by io.github.blackboxfoundry

bank_health_report

Read-onlyIdempotent

One-call financial-health read for a US bank or savings institution. Give a bank name or an FDIC certificate (CERT) number. Joins FDIC BankFind institution + financials (total assets, deposits, net income, return on assets/equity, active-vs-failed status) with the CFPB Consumer Complaint Database (complaint volume and top complaint products for the matched company) into a HEALTHY / STABLE / WATCH / FAILED read with the numbers behind it. FDIC is the primary signal; CFPB complaint data is best-effort and degrades gracefully if the bank's complaint records cannot be matched. Useful for picking a sponsor/partner bank, treasury counterparty checks, or deposit-safety questions. Informational, not a rating or advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bankNoBank or savings institution name (e.g. 'JPMorgan Chase Bank', 'Cross River Bank'). Use the full legal name for best matching.
certNoOptional FDIC certificate (CERT) number for an exact institution match, used instead of a name.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds genuinely useful behavioral context: FDIC is the primary signal, CFPB complaint data is best-effort and 'degrades gracefully' when a bank match is missing, and the result is 'informational, not a rating or advice.'

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?

The description is dense but well-organized: purpose first, then input, data sources, output, use cases, and disclaimer. Every sentence adds distinct information and none of it is filler or repetition of the schema.

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

Completeness5/5

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

Even without an output schema, the description tells an agent what the response contains: total assets, deposits, net income, return on assets/equity, active-vs-failed status, complaint volume, top complaint products, and an overall health category. It also covers the fallback behavior and appropriate use cases, making it fully actionable for invocation.

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?

The input schema already provides 100% documentation for both parameters, including the full legal name tip and the exact-match behavior of CERT. The description only restates the bank-name-or-CERT input concept without adding new syntax, defaults, or interaction rules, so it meets the baseline but does not exceed it.

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 uses a specific verb and resource: 'One-call financial-health read for a US bank or savings institution.' It clearly states the composite nature of the tool (FDIC + CFPB) and the output categories (HEALTHY / STABLE / WATCH / FAILED), which distinguishes it from raw FDIC or CFPB sibling tools without needing to inspect them.

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 gives concrete use cases: 'picking a sponsor/partner bank, treasury counterparty checks, or deposit-safety questions.' It does not explicitly name alternatives like fdic_financials or cfpb_complaint_aggregations or say when not to use this tool, but the 'one-call' composite framing implies it is the go-to for a combined health read.

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

B3.2/5.0
Disambiguation2/5

Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.

Naming Consistency3/5

The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.

Tool Count1/5

290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.

Completeness4/5

For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.

Resources