Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations mark this non-read-only and non-destructive, and the description adds real substance beyond them: what gets created (user-owned, editable dataset + rubric), what is returned (both ids), and the exact permissions required (caliper:datasets:write, caliper:evals:write). Does not mention idempotency or what happens if the slug already exists.

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?

Two tight sentences: the action and result come first, then the next step and prerequisites. Zero filler.

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?

Covers the mutation, its outputs (both ids), the follow-up tool, and permission requirements, which is sufficient for a 3-param install tool with no output schema. Missing only edge-case behavior such as re-installing an existing slug.

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 description coverage is 100%, with the slug enum documented and sourced to caliper_starters_list, so the schema carries the burden. The description's mention of 'returns both ids' adds nothing about the workspace override or approvalId flow, so baseline 3 applies.

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 a specific verb (copies/installs) plus the concrete resources produced (a new dataset and a new rubric the user owns). An agent can distinguish this from caliper_starters_list (read-only listing) and caliper_datasets_create (blank dataset) without opening any 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?

Clearly frames the workflow: install a starter, then bind the returned ids via caliper_evals_create. It does not explicitly say when to choose this over caliper_datasets_create or caliper_rubrics_create, but the context is unambiguous for a starter-based workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.