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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world. The description adds genuinely new context beyond them: 'reads no workspace data' clarifies there are no data prerequisites, and 'get concrete improvement suggestions' indicates the kind of output returned.

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?

Three short sentences, front-loaded with what the tool does, followed by side-effect profile and usage trigger. Every sentence earns its place with no 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?

For a simple, read-only, no-output-schema analysis tool, the description covers purpose, side effects, and timing adequately. The one real gap is the undocumented input parameters, which the description does not fill.

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 only 33% — only 'detailed' is documented, while 'title' and 'description' have no schema descriptions. The tool description never compensates for this, giving no hint about what 'title' vs 'description' should contain or their length limits.

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+resource ('Score a proposed objective') and the exact rubric applied (SMART), plus the concrete value delivered ('improvement suggestions'). No sibling tool performs scoring, so it is unambiguously distinct from the create/update/list tools in the set.

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?

Gives an explicit workflow trigger: 'Use it before proposing OKRs to raise their quality,' which ties it to the sibling propose_okr_set. It does not state when the tool is unnecessary or name a contrasting alternative, so it stops short of a 5.

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