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Industry Vocabulary

industry-vocabulary

Industry Vocabulary — Hand it a trade or industry in plain words and get back the language that industry actually uses: what a caller is called, what the appointment is called, what the provider is called, and the questions that qualify a job. Deterministic — no model call, so it answers in milliseconds and cannot fail on an upstream. Says plainly whether it matched a real vertical or fell back to generic. (1 MESH/call, a tool · business)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesPlain JSON POST body (not MCP). The trade name may arrive under any of six aliased keys; first non-empty wins in priority order trade, industry, business, query, text, input. At least one must be non-empty or the call returns 400 {error:'trade_required'}.

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the minimal annotations (readOnlyHint: false, openWorldHint: true, destructiveHint: false), the description discloses key behaviors: deterministic (no model call), fast (milliseconds), cannot fail on an upstream, fallback handling (says whether matched a real vertical or generic), and cost (1 MESH/call). This adds significant transparency and does not contradict annotations.

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 three sentences, front-loaded with the purpose, and every sentence earns its place. It covers input, output, determinism, fallback, and cost without fluff. This is appropriately sized for the tool's simplicity.

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 no output schema, the description adequately describes the return value by naming the fields returned (caller, appointment, provider, qualifying questions) and the fallback indicator. It also covers performance, cost, and failure characteristics. Given the tool's low complexity, the description is complete for an agent to use it effectively.

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?

The input schema is exceptionally thorough, covering all aliases, priority order, trimming, truncation, and error cases (100% coverage per context signals). The description adds only that the input is a 'trade or industry in plain words,' which is already stated in the schema. Since schema coverage is high, the baseline 3 applies; the description offers no additional parameter-level meaning.

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 and resource: 'Hand it a trade or industry in plain words and get back the language that industry actually uses.' It clearly lists the outputs (caller, appointment, provider, qualifying questions), which distinguishes it from sibling tools focused on analysis, discovery, or memory.

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 clear context: use this to translate a plain-language industry into industry-specific vocabulary. It does not explicitly mention when not to use it or alternative tools, but the deterministic, fast, and fallback-aware behavior implies its niche. No exclusions are given, but the context is clear enough for an agent to decide when to invoke it.

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

B3.4/5.0
Disambiguation2/5

Several tools have overlapping purposes: search and mesh_discover both enumerate the catalog, while biz-analyze, task-analysis, and task-orchestrate all produce structured plans from a described situation. This will cause agents to misselect between them despite otherwise distinct tools.

Naming Consistency2/5

Naming is inconsistent: mesh_* tools use snake_case, most capability tools use hyphenated lowercase names, and a few (fetch, search) are bare verbs. There is no single verb-object or noun-verb pattern that holds across the set.

Tool Count3/5

28 tools is on the heavy side, but the marketplace concept justifies including many callable capabilities. However, the mix of platform tools and unrelated utilities makes the surface feel cluttered and hard to navigate.

Completeness4/5

The core marketplace lifecycle is well covered: signup, discover, fetch, publish, delegate, refer, follow, subscribe, and balance. Minor gaps exist (no unpublish or edit for listings), but most agent workflows can proceed without dead ends.