create_sample_projectCreates a sample client, a sample project with a budget, six tasks with estimates and two weeks of hours, labelled as a sample in its name, so reports, the budget bar and the timesheet have something to show. One at a time. Uses a board of the free plan's limit (and the sample client is left out if the client limit is full).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare write, non-open-world, and destructive behavior, but the description adds rich operational detail about exactly what gets created, how much (six tasks, two weeks of hours), the 'one at a time' constraint, and free-plan/client-limit fallbacks. It does not explain the destructive aspect hinted by annotations (e.g., whether existing sample data is replaced), leaving a small gap.
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 front-loaded and concise overall, but the first sentence is a long, multi-clause run-on that could be split for easier parsing. The second and third sentences are short. Overall efficient with no fluff.
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?
Given no input schema, no output schema, and annotations that carry the safety profile, the description supplies the necessary operational context: what the sample project comprises, its labelling, concurrency limit, and quota interactions. It is nearly complete; only the destructive annotation's implication is left unexplained.
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?
Zero parameters, so the schema imposes no semantic burden; baseline for no-param tools is 4. The description correctly focuses on side effects rather than field-level semantics.
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?
States the verb 'Creates' and precisely enumerates the resources (sample client, sample project with budget, six tasks, two weeks of hours) while marking the output as sample-labelled, which clearly separates it from create_project/create_client siblings that produce real data. An agent can identify the tool's unique role without opening the schema.
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?
Provides clear context for use – populating reports, budget bar and timesheet with demo data – and a usage constraint ('One at a time'), plus limitation about free-plan board and client limit. It does not name when to avoid it or point to alternatives, so it stops short of the top score.
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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