List formal enforcement actions and penalties taken against a facility, plus a per-program summary of formal/informal actions, cases, and total penalties. Requires an EPA Registry ID (use epa_facility_search to find it).
| Name | Required | Description | Default |
|---|---|---|---|
| registry_id | Yes | EPA Registry ID (FRS ID), the numeric facility identifier returned by epa_facility_search (e.g. '110001136271'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive, so the safety profile is covered. The description adds useful output context (per-program summary, penalties) and a prerequisite, but doesn't disclose other behavioral traits such as pagination, data freshness, or limitations beyond the safe-read nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences: the first delivers the full purpose and data contents, the second states the required prerequisite and how to satisfy it. There is no repetition of schema information or filler text; every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read-only tool with no output schema, the description gives enough context: what data is returned (actions, penalties, per-program summary), what input is needed, and how to get that input. Minor gaps, like whether the result list is paginated or what happens for invalid IDs, are not critical for basic selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the parameter schema already explains what registry_id is, how to obtain it, and provides an example. The tool description adds no parameter-level meaning beyond what the schema offers, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('List') and resource (formal enforcement actions and penalties against a facility), and adds a distinctive summary component. It doesn't explicitly contrast itself with siblings like epa_facility_compliance or epa_water_or_air_violations, so it falls just short of full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it—when you have a Registry ID and want enforcement actions—and names the prerequisite lookup tool (epa_facility_search). However, it does not state when not to use it or mention alternatives for related but distinct needs (e.g., compliance status), leaving comparison to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.