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environmental_site_risk

Read-onlyIdempotent

One-call environmental-compliance and contamination liability read for a SPECIFIC site or operator - the question a buyer, lender, or Phase-I ESA asks before a deal. Distinct from location_risk_report (which scores natural hazards plus a shallow count of nearby facilities): this drills DEEP into one named facility's EPA record via ECHO/FRS - overall compliance status, per-statute program standing (Clean Air/Water/RCRA/etc.), formal enforcement actions and penalty totals, significant-non-compliance and non-compliant-quarter flags - plus a best-effort parcel record for site context. Returns a verdict band (NO ADVERSE EPA RECORD / REVIEW RECOMMENDED / CONTAMINATION-COMPLIANCE CONCERN / NO FACILITY FOUND), the flags, and the evidence. A source that fails is noted, not fatal. This is an EPA public-record screen, not a Phase-I Environmental Site Assessment or a substitute for one. Premium cross-source synthesis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesSite, facility, or operator name to screen (e.g. 'Smith Manufacturing', 'Acme Plating Inc').
stateNoOptional 2-letter state to disambiguate the EPA facility and parcel search.
addressNoOptional street address to pin the parcel record.

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses that a failing source is 'noted, not fatal,' that the parcel record is 'best-effort,' and that it is a public-record screen via ECHO/FRS. This gives the agent realistic expectations about completeness and partial data without contradicting annotations.

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?

The description is dense and front-loaded with purpose, followed by disambiguation, output contract, and caveats. It is slightly long and ends with the promotional 'Premium cross-source synthesis' tagline, which adds little functional guidance, but the rest is information-dense.

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 lists the exact verdict-band values, the flagged data categories, and the evidence returned. Combined with the optional state/address parameters for disambiguation, an agent has enough context to invoke the tool and interpret its result appropriately.

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 documents all three parameters and schema coverage is 100%, so the baseline is 3. The description reinforces that the tool targets a 'specific site or operator' but adds no new parameter-level syntax or format details beyond the schema.

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 opens with a specific resource and intent: 'environmental-compliance and contamination liability read for a SPECIFIC site or operator' and names the exact output (verdict band, flags, evidence). It also differentiates itself from location_risk_report, so an agent can tell which tool answers a compliance/contamination question versus a natural-hazard screen.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states when to use it ('the question a buyer, lender, or Phase-I ESA asks before a deal') and when not to ('not a Phase-I Environmental Site Assessment or a substitute for one'). It explicitly names the closest alternative, location_risk_report, and explains the depth distinction.

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