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salesnav_resolve_industry

Read-onlyIdempotent

Resolve an industry name (any language) to its LinkedIn Industry Code(s) using the bundled Industry Codes V2 taxonomy (offline, no LinkedIn call). Returns ranked candidates with id, label and hierarchy path. Use the returned id(s) in salesnav_build_search_url's industry filter. Call once per industry term; if several candidates look plausible, pick by the hierarchy path. Use for industries only (offline taxonomy, any language, no LinkedIn call); for locations, companies, schools and titles use salesnav_typeahead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of rows to return.
queryYesIndustry name to look up, e.g. 'software', 'banque', 'real estate'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
candidatesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive/closed-world; the description adds meaningful context beyond them: it is offline with no LinkedIn call, and it returns ranked candidates rather than a single answer. Minor gap is that it doesn't say what happens on an ambiguous or unmatched term.

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 return shape, then usage. Slightly repetitive – the parenthetical 'offline, no LinkedIn call' restates the earlier 'offline, no LinkedIn call' – costing a bit of tightness.

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?

With an output schema covering the return fields and rich annotations covering safety, the description supplies exactly the missing pieces: the offline/any-language scope, cadence, disambiguation heuristic, and sibling routing. Nothing an agent needs to call it correctly is absent.

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 description coverage is 100%, so query and limit are already documented including examples and bounds. The description adds the important 'any language' semantic but nothing further about limit or ranking behavior, so baseline 3 applies.

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?

States a specific verb (resolve) and resource (industry name → LinkedIn Industry Code) plus the mechanism (bundled Industry Codes V2 taxonomy, offline). Explicitly distinguishes itself from salesnav_typeahead for non-industry entity types.

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?

Names the downstream consumer (salesnav_build_search_url's `industry` filter), gives calling cadence (once per term), a disambiguation rule (pick by hierarchy path), and explicit exclusions that route to salesnav_typeahead for locations/companies/schools/titles.

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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