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LiveDataLink

by io.github.blackboxfoundry

eia_series_lookup

Read-onlyIdempotent

Flexible EIA series lookup. Pass any EIA series ID (e.g. 'PET.RWTC.D' for WTI crude daily, 'NG.RNGWHHD.D' for Henry Hub spot daily, 'ELEC.PRICE.US-ALL.M' for US average electricity retail price monthly). Returns time-series data for that series. Use this when no other tool covers your specific need.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoInclusive upper-bound period (ISO date or YYYY-MM).
limitNoMaximum rows to return (default 50, max 5000).
startNoInclusive lower-bound period (ISO date or YYYY-MM depending on series cadence).
series_idYesEIA series ID. See https://www.eia.gov/opendata/browser/ for the full catalog.

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that it accepts any series ID and returns time-series data, but it does not disclose output shape, error behavior, cadence handling, or any rate-limit concerns.

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?

Three compact, front-loaded sentences: purpose, examples, return type, and usage guidance. There is no redundant wording or filler.

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?

For a simple read-only lookup with one required parameter and a fully documented schema, the description is mostly complete. It communicates the open-world nature, gives representative IDs, and states the return type; it does not describe output formatting or invalid-ID behavior, but those are minor for this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description goes further by giving concrete series_id examples with their frequencies (daily and monthly). This adds practical meaning beyond the schema's generic 'EIA series ID' and catalog link.

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 clearly states this is a flexible EIA series lookup that accepts any EIA series ID and returns time-series data. Concrete examples (WTI crude, Henry Hub, electricity price) reinforce the resource and scope. It distinguishes itself from more specific EIA sibling tools by framing itself as the catch-all option.

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 an explicit usage rule: 'Use this when no other tool covers your specific need.' This gives clear context for when to choose this tool, but it does not name specific sibling alternatives or explicitly state when not to use it beyond that general principle.

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