The wage-vs-cost join: what an hourly wage actually leaves over each month in every Saskatchewan community, after tax, housing, utilities and commuting. Pass occupation (models its median wage, with posting counts; their truth state is in meta.evidence) or wage.
| Name | Required | Description | Default |
|---|---|---|---|
| wage | No | Explicit hourly wage, CAD. | |
| occupation | No | Role id from list_roles. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It explains the core computation but omits details like whether it is read-only, requires authentication, or has limits. The mention of 'meta.evidence' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence. It could be more clearly structured (e.g., separate sentences for purpose and parameter guidance), but it conveys the essential meaning without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should explicitly state what the tool returns (e.g., list of communities with leftover amounts). It only implies the output. Also, it does not clarify that both parameters are optional but at least one is needed, creating ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters. The description adds that occupation models median wage and mentions 'meta.evidence', providing mild extra context, but does not fully explain the 'role id' format or how wage is used.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes disposable income after costs like tax, housing, and commuting, specific to Saskatchewan communities. This distinguishes it from siblings like get_wages or get_real_estate, though the phrasing 'wage-vs-cost join' is slightly opaque.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. It only explains that either occupation or wage must be passed, but does not clarify scenarios where one is preferred or warn against using it for other purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.
