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opportunity-exchange

by ca.veilpoint

get_wages

Measured wages and vacancies (Statistics Canada, real data): LFS median/average hourly wages by occupation group × province, and JVWS job vacancies with average offered hourly wage by NOC 2021 unit group × province/territory. Pass noc for one unit group across geographies, province for one geography, both for one cell, neither for the national overview. Wage medians are group-level; each estimate names the published grouping that answered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nocNoFive-digit NOC 2021 unit-group code from list_noc_groups.
provinceNoSGC 2021 code, postal abbreviation (e.g. SK), or "canada".

TDQS

A4.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It notes data is 'real data' from Statistics Canada and clarifies that wage medians are group-level, adding some transparency. But it omits details on update frequency, authorization needs, or potential rate limits, which would help an agent.

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 a single paragraph of four sentences, front-loaded with the core purpose. Every sentence adds value with no redundancy 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?

The tool has no output schema, so the description should compensate. It covers all parameter usage modes and mentions that results include grouping names, but does not describe the return format or data structure (e.g., table, JSON). Still, for a simple retrieval tool, it is mostly complete.

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. The description adds substantial meaning beyond schema: it explains the effect of passing none, one, or both parameters, and clarifies that wage medians are group-level with published grouping names.

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 the tool returns wage and vacancy data from specific Statistics Canada datasets (LFS, JVWS) with dimensions like occupation group and province. It implicitly distinguishes from sibling tools by focusing uniquely on wages and vacancies, which are not covered by other tools.

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 explicit guidance on parameter combinations: pass noc for geographies, province for one geography, both for one cell, neither for national overview. It does not, however, mention when not to use this tool or suggest alternatives.

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

B3.1/5.0
Disambiguation1/5

Several tools are effectively duplicates or near-duplicates: get_emerging_signals is an explicit alias for list_economic_signals, resolve_entity and resolve_entities overlap heavily, and the markdown variants duplicate their non-markdown reports. Pairs like compare_communities/compare_municipalities and search_businesses/search_licensed_businesses also require reading long contracts to avoid misselection.

Naming Consistency4/5

Tool names overwhelmingly follow a snake_case verb_noun pattern with sensible verbs like get_, list_, search_, and compare_. The main deviations are the backwards-compatible get_emerging_signals alias and prefix choices such as check_business_health vs get_business_health that obscure the underlying distinction.

Tool Count1/5

70 tools is an extreme surface for any MCP server, far beyond the 25+ 'too many' threshold. The set is fragmented by format variants, aliases, and multiple overlapping lookup tools, making selection and maintenance costly.

Completeness3/5

The domain surface is broad: entity resolution, business health, labour, community economy, procurement, and governance evidence are all covered in depth. However, there are notable lifecycle gaps—no sandbox deletion, consent revocation, health-action cancellation, or actual exchange/connect/apply step—that leave agents with dead ends.

Resources