Evidence availability and confidence-gate work queue for all 17 Saskatchewan cities and 149 towns. Returns current Tier A–D counts, evidence-domain coverage, public-model input counts, local-context status and the next defensible data action for each municipality.
| Name | Required | Description | Default |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the tool is a read-style reporting tool ('Returns current counts...'). However, it doesn't state whether this is a read-only operation or whether the 'next defensible data action' could trigger mutations or writes. With no annotations provided, the description partially carries the transparency burden but leaves ambiguity about side effects.
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?
Single sentence serving both as overview and scope definition. It's front-loaded with the key purpose (evidence availability work queue) followed by the specific data points returned. Compact and dense with information, though slightly long as one sentence.
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?
For a no-parameter, no-output-schema reporting tool, the description covers the main scope (all municipalities), the key output dimensions (Tier counts, coverage, model inputs, context status, next action), and the data granularity. It doesn't describe the return format, but with no output schema and a broad listing tool, the description is reasonably complete. Could mention sorting or filtering behavior but this is a minor gap.
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?
There are 0 parameters, so the schema provides no parameter information at all. Schema coverage is 100% only because there are no parameters to cover. The description adds context about what all municipalities are included (17 cities, 149 towns), which effectively documents the implicit scope of the no-parameter call. With 0 params, the baseline is 4 per the rubric, and the description does clarify the full coverage scope.
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 what it does: returns a work queue of evidence availability and confidence-gate status for Saskatchewan municipalities. The verb 'returns' plus specific fields (Tier A-D counts, coverage, model inputs, local-context status, next action) make the purpose concrete. It doesn't explicitly distinguish from siblings like get_community_economy, but the domain (municipality evidence coverage) is distinct enough from the economic/role/job tools.
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?
The description implies when to use: when assessing evidence readiness or confidence-gating for municipalities/communities. It names the scope explicitly (17 cities, 149 towns) but doesn't give explicit when-not-to-use guidance or name alternative tools for similar needs. Given zero annotations and no other guidance, the usage context is implied rather than explicit.
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.
