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Look up substances by name

search_substances
Read-only

Look up substances by name on one regulatory axis (same as HTTP GET /v1/substances?name=…). The name is normalised (NFKC, whitespace removed, lower-cased) and matched exactly against the names and aliases the axis itself uses in that language (E numbers and official names for EU, 品目名 and label terms for JP, CFR names for US) — no partial or fuzzy matching. The official name is an alias of itself. Returns the matching substances (SubstanceSummary: facts from their own roster only) and, per row, what text matched. axis and lang must be one of the accepted pairs: JP+ja, US+en, EU+nl, EU+fr, EU+de, EU+es, EU+pl, EU+el, EU+bg. Not a safety judgement: every record is a draft and needs verification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
axisYesRegulatory axis the label or name belongs to: JP, EU or US.
langYesLanguage of the name or label text (ISO 639-1), e.g. ja, en, de, fr.
nameYesThe name to look up, as printed on a label or roster.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

With readOnlyHint/openWorldHint already covering the safety profile, the description adds substantial non-obvious behavior: NFKC normalisation, exact-only matching against axis-specific name sets, what the response rows contain (SubstanceSummary plus the matched text), and an explicit caveat that records are drafts requiring verification.

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?

Front-loaded with the core action and matching semantics, and the dense sentences each carry information rather than filler. It is still a fairly long block for a three-parameter lookup, and the HTTP GET parenthetical is conveniences rather than essentials.

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?

There is no output schema, so the description appropriately explains the return shape (matching SubstanceSummary rows plus the matched text). Combined with the draft-verification caveat and the axis/lang constraint, an agent has everything needed to invoke and interpret this correctly.

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

Parameters5/5

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

Schema coverage is 100%, so baseline is 3, but the description materially exceeds the schema by constraining axis+lang to an enumerated pair list (the schema has no enums) and by explaining what each axis's vocabulary actually contains (E numbers for EU, 品目名 for JP, CFR names for US) and how the input name is transformed before matching.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('look up substances by name') scoped to one regulatory axis, and the exact-match semantics clearly frame it as a name-lookup rather than an ID fetch. It does not explicitly name or contrast itself with the sibling get_substance, so the differentiation is only implied.

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

Usage Guidelines3/5

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

The description implies the use case (resolve a printed name or label term to substances) but never states when to use this versus get_substance or the analyze_label family, nor any when-not condition. The accepted axis/lang pair list gives practical invocation guidance but is not routing 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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