Get Project Usage
get_project_usageGet resource usage metrics (CPU, memory) for a project
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | Project ID (UUID) |
get_project_usageGet resource usage metrics (CPU, memory) for a project
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | Project ID (UUID) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. However, the description adds no extra behavioral context such as permissions, time-range constraints, or rate limits, offering nothing beyond what structured data already indicates.
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, focused sentence that immediately conveys the action, resource, and scope. Every word contributes meaning with no fluff or repetition of the tool name.
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?
The tool is simple with one well-documented parameter and good annotations, so the description is mostly sufficient. However, there is no output schema and the description omits details like whether metrics are real-time, units, or response format, leaving some ambiguity for an agent. It is minimally complete but not rich.
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?
Schema coverage is 100% with a clear description for project_id ('Project ID (UUID)'). The description only says 'for a project', which adds no additional meaning beyond the schema, so the baseline score of 3 is appropriate.
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 verb 'Get' and the specific resource ('resource usage metrics (CPU, memory)') for a project, making it distinct from sibling tools like get_project or get_graph_statistics. It precisely answers what the tool does.
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 the tool should be used when needing CPU/memory usage for a project, but it does not explicitly state alternatives or when not to use it. There is no comparison to sibling get_* tools, but the usage scenario is reasonably inferable.
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.
Most tools are clearly differentiated by domain (project vs graph_project) and action (create, get, list, delete). The main ambiguity is get_project vs get_project_info, which both claim to return detailed project information. Otherwise tool boundaries are clear.
The server follows a strong verb_noun convention, with parallel naming for graph and non-graph tools (create_project/create_graph_project, deploy_staging/deploy_graph_staging). Minor deviations include bulk_create_graph_nodes and fulltext_search_graph, but patterns remain predictable.
48 tools is a heavy surface, even when accounting for the two parallel product domains (relational and graph). Many tools are near-duplicates across domains, and the count exceeds the 25-tool threshold that feels manageable. It would benefit from consolidation or sub-servers.
Both project types have full life-cycle coverage: create, schema management, deployment, rollback, and deletion, plus graph data operations including bulk, search, and traversal. Minor gaps exist, such as no update_graph_relationship and the redundant get_project/get_project_info pair, but agents can accomplish core workflows.