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Epa Regulations

by io.github.pipeworx-io

Epa Search

epa_search
Read-onlyIdempotent

Keyword search across EPA regulations — US Environmental Protection Agency rules in 40 CFR. Answers "what EPA regulations cover X", "the environmental regulation / EPA rule about X", "find the EPA requirement for X". Great for topics: hazardous waste identification (RCRA), emission standards and air quality (Clean Air Act), NPDES water discharge permits (Clean Water Act), drinking water standards, air toxics / NESHAP, toxic substances (TSCA), Superfund / CERCLA, pesticide registration (FIFRA), greenhouse gas reporting requirements, underground storage tanks, stormwater. Returns matching EPA regulations with citation (40 CFR), heading, excerpt, and source URL. This searches EPA REGULATIONS (regulatory text); for EPA DATA (facility enforcement, ECHO, GHG emissions figures) use the epa-echo / epa-emissions tools. Example: epa_search({ query: "hazardous waste identification" }); epa_search({ query: "emission standards", limit: 15 }). Keyless.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return, 1-20 (default 10).
queryYesEnvironmental-regulation topic or phrase, e.g. "hazardous waste identification", "emission standards", "NPDES permit", "drinking water", "toxic substances".

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate read-only and idempotent. Description adds return format details (citation, heading, excerpt, source URL) and notes 'Keyless', providing useful context beyond 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?

Well-structured with front-loaded purpose, use cases, and examples. Slightly verbose but each sentence adds value.

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?

Given no output schema, description thoroughly covers return fields, domain (40 CFR), and keyless access. Includes examples and differentiates from data retrieval 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 covers both parameters with descriptions (100% coverage). Description adds examples and context but does not significantly enhance meaning beyond 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?

Description clearly states verb ('search'), resource ('EPA regulations'), and scope ('40 CFR'). Provides specific examples and distinguishes from sibling tools (epa-echo/epa-emissions).

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?

Explicitly states when to use ('what EPA regulations cover X') and when not to ('for EPA DATA use...'). Lists relevant topics and provides alternative tools.

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

A3.6/5.0
Disambiguation2/5

The server includes many overlapping tools (e.g., multiple ask_pipeworx variants, epa_regulation vs. epa_search vs. discover_tools). More critically, the tool set covers vastly different domains (Polymarket bets, npm packages, AI visibility, memory storage) alongside EPA regulations, making it hard for an agent to distinguish purposes.

Naming Consistency2/5

Tool names use a mix of styles: underscore (epa_regulation, ask_pipeworx), camelCase (deep_research, suggest_questions), and verb phrases (scan_competitor_ai_presence). No consistent pattern is followed across the set.

Tool Count2/5

33 tools is high for a server named 'Epa Regulations'. The vast majority are unrelated to EPA regulations (e.g., Polymarket, npm scanning, memory functions), making the scope mismatched. A focused server should have fewer, domain-specific tools.

Completeness1/5

For a server claiming to be about EPA regulations, only two tools (epa_regulation, epa_search) are directly relevant. The rest are from unrelated domains, leaving severe gaps in expected functionality like rule updates, compliance checks, or cross-referencing with other environmental data.

Resources