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LiveDataLink

by io.github.blackboxfoundry

chemical_lookup

Read-onlyIdempotent

Resolve a chemical name (e.g. 'aspirin', 'caffeine') or a PubChem CID to its core identity and physical properties using the NIH/NLM PubChem public database (keyless, public-domain data). Returns the PubChem Compound ID (CID), IUPAC systematic name, molecular formula, molecular weight (g/mol), and the canonical SMILES structure string. Use it to disambiguate a substance and obtain a stable CID join key for further chemistry or safety lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesA chemical name (e.g. 'aspirin', 'sodium chloride') or a numeric PubChem CID (e.g. '2244').

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, open-world, and non-destructive behavior. The description adds non-redundant context: the external NIH/NLM PubChem dependency, keyless access, and public-domain data source. It does not mention rate limits or failure behavior, but the annotation coverage lowers the burden.

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 sentences with front-loaded purpose, then explicit return fields, then downstream use case. The description contains no filler or redundancy; each sentence earns its place.

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?

For a single-parameter lookup with no output schema, the description fully covers input forms, data source, exact return fields, and intended downstream use. Nothing required to select or invoke the tool correctly is missing.

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% and the query parameter already documents the accepted forms: a chemical name or a numeric PubChem CID, with examples. The description's examples largely repeat the schema, adding only 'caffeine' and reinforcing high-level purpose, so it provides no substantive new parameter semantics.

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 uses a specific verb ('Resolve') with a clear resource (chemical names or PubChem CIDs via PubChem) and enumerates exact outputs (CID, IUPAC name, formula, MW, SMILES). It also positions itself as an identity-resolution and CID-join-key provider, distinguishing it from downstream chemistry or safety lookups such as the sibling chemical_hazards.

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?

It gives an explicit use directive: 'Use it to disambiguate a substance and obtain a stable CID join key for further chemistry or safety lookups.' However, it does not name an alternative tool or state when not to use it, so it stops short of full when/when-not guidance.

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