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fdic_search_institutions

Read-onlyIdempotent

Search FDIC-insured banks and savings institutions by name, state, or city. Returns CERT number, name, location, total assets, deposits, net income, ROA, ROE, charter class. Use the CERT number for follow-up queries to fdic_financials or fdic_history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity name (exact)
nameNoInstitution name (partial match)
limitNoMax results (default 25)
stateNoTwo-letter state code (e.g. 'CA', 'TX')
offsetNoPagination offset (default 0)
active_onlyNoOnly currently-active banks (default true)

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds behavioral context beyond annotations by specifying the returned metrics and the workflow tie-in with CERT-based follow-up tools. It doesn't contradict the annotations.

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 two sentences, front-loads the core purpose and search criteria, then gives actionable follow-up guidance. Every sentence earns its place with no filler or redundancy.

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?

The tool is a straightforward read-only search with all six parameters fully described in the schema and safety covered by annotations. The description adds the result field list and follow-up workflow, so an agent has enough to invoke it correctly and route to related tools.

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 description does not need to re-document parameters. It adds value by mentioning that search is by name, state, or city, which roughly maps to the name, state, and city parameters, but otherwise it doesn't provide semantic detail beyond what the schema already contains. Baseline 3 is appropriate.

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 names a specific verb and resource: 'Search FDIC-insured banks and savings institutions', and specifies search criteria (name, state, city). It also enumerates the returned fields (CERT number, name, location, total assets, deposits, net income, ROA, ROE, charter class), making the tool's function concrete and easy to distinguish from sibling FDIC tools.

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 provides clear context: use this tool to search institutions by name, state, or city, then use the CERT number for follow-up queries to fdic_financials or fdic_history. It does not explicitly state when not to use this tool or alternatives such as directly querying fdic_financials for a known CERT, but the follow-up instruction gives practical routing guidance.

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.

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