check-current-projectReturn the currently saved team_domain and facility_key for this user.
| Name | Required | Description | Default |
|---|---|---|---|
| user_intent | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / user_intentAdded value: +{
+ "default": "",
+ "title": "User Intent",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description adds useful context by specifying the exact return fields (team_domain and facility_key) and that it is for 'this user'. No contradiction exists, and the behavior is adequately transparent for a simple read operation.
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 sentence, starts directly with the verb 'Return', and contains no unnecessary words. It is concise, front-loaded, and 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.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only getter, the description covers the core functionality and return fields. The output schema exists to detail return structure. However, the unexplained 'user_intent' parameter and lack of mention of behavior when no project is set create minor gaps, preventing a perfect score.
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 schema has one optional parameter 'user_intent' with no description, and schema description coverage is 0%. The tool description does not mention this parameter at all, leaving its purpose and expected values entirely unexplained. Since the description must compensate for low schema coverage, this is a significant gap.
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 uses the specific verb 'Return' and identifies the exact resources ('currently saved team_domain and facility_key'), clearly stating the tool reads the current project context. This distinguishes it from siblings like set-focus-project (which modifies the project) and list-my-projects (which lists all projects).
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 title 'See which project the conversation is currently focused on' communicates a clear use case, and the description reinforces it by specifying the saved fields. However, it does not explicitly name alternatives or state when not to use this tool, relying on context from sibling tools.
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.
Tools generally have distinct purposes, but there is overlap between analyze-progress-and-forecasts and ask-about-project-data for progress metrics, and between search-site-photos and ask-about-project-data for capture data. The descriptions include guidance (e.g., 'use analyze-progress for trade visibility'), but an agent may still be uncertain which tool to choose for a given query.
All tool names use a consistent lowercase hyphen-separated format with a verb prefix (e.g., list-my-projects, set-focus-project). Most follow a verb-noun structure, though ask-about-project-data and analyze-progress-and-forecasts include prepositions/conjunctions, making them slightly less uniform.
With 7 tools, the server is well-scoped for its purpose: four analysis tools and three context-management tools. Each tool serves a clear role without unnecessary redundancy, and the count aligns well with typical MCP server conventions.
The tool set covers the core needs of project progress analysis, natural language querying, photo search, findings comparison, and project context management. Access to detailed records is available through ask-about-project-data, so no major dead ends. Minor gaps include no dedicated tool for just listing captures or viewing project details, but these are addressable via the query tool.