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NREL AFDC — Alt-Fuel Stations Search

nrel.afdc.search
Read-onlyIdempotent

Search US alternative fuel stations by ZIP code, state, or city. Filter by fuel type, EV connector, and access level for state-level analytics or city-wide EV infrastructure surveys.

Instructions

Search US alt-fuel stations by ZIP, state, or city. Filterable by fuel type, EV network, connector type, and access level. Use for state-level analytics or city-wide EV infrastructure surveys; use afdc_stations_nearest for proximity search to a coordinate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNo5-digit US ZIP code to search within. Example: '94102'.
stateNo2-letter US state code. Example: 'CA', 'TX', 'NY'.
cityNoCity name. Use with state for disambiguation. Example: Oakland.
fuel_typeNoComma-separated fuel codes: ELEC (electric), CNG, LNG, LPG (propane), BD (biodiesel), E85, HY (hydrogen). Default ELEC.ELEC
ev_connector_typeNoEV connector codes (comma-separated): J1772 (Level 2), J1772COMBO (CCS), CHADEMO, TESLA, NEMA1450, NEMA515.
accessNoFilter by access type: 'public' for open-access stations, 'private' for fleet-only.
statusNoStation status: E=available (open), P=planned (future), T=temporarily unavailable. Default E.E
limitNoResults per page (1-200). Default 50.
offsetNoPagination offset — number of results to skip. Default 0.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds no contradictory information and provides some additional context about filtering capability, but does not elaborate on pagination, response format, or other behavioral details beyond what the schema already covers.

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 long, front-loaded with action and resource, and contains no redundant or extraneous information. Every word contributes to clarity and conciseness.

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

Completeness4/5

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

Given the high schema coverage (100%) and presence of output schema, the description covers essential purpose and use cases. It misses mentioning the need to pair city with state for disambiguation (though schema notes this), but overall provides sufficient context for effective use.

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 coverage is 100% with detailed descriptions, examples, and enums for each parameter. The description only mentions high-level filter categories (fuel type, EV network, connector type, access level) without adding new semantics or clarifying nuances beyond the schema. Baseline score of 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 starts with the verb 'Search' and specifies the resource ('US alt-fuel stations') and key dimensions (ZIP, state, city, fuel type, etc.). It clearly distinguishes from the sibling 'afdc_stations_nearest' by stating the latter is for proximity searches, making the purpose unambiguous.

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?

The description explicitly states suitable use cases: 'state-level analytics or city-wide EV infrastructure surveys'. It also names an alternative tool ('afdc_stations_nearest') and explains when to use that instead, providing clear guidance on selection between sibling 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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