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

Annotations already declare readOnly/openWorld=false/destructive=false, so safety is covered. The description adds real context beyond them: items are starting points that a workspace may rename and retarget, and adoption happens through a separate tool. It stops short of pagination or size limits, but for a small read-only catalog that is a minor 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?

Front-loaded with what the tool returns, then when to use it, then filtering, then delivery guidance. Every sentence carries information, though the block is dense enough that it spans several distinct concerns; still efficient for the amount of guidance an agent needs.

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?

There is no output schema, but the description compensates by enumerating the fields each preset contains and clarifying these are editable starting points. Combined with annotations covering the safety profile, an agent has everything needed to call and use this tool correctly.

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 both enums documented, so baseline is 3. The description goes further by explaining the semantic distinction between the two filters — facet = where it lives in the business, tag = what kind of number it is — which helps an agent choose the right filter rather than just read the enum values.

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 ('ready-made metrics a business can start tracking') and enumerates what each item carries (unit, cadence, good direction, facet, tags). It also implicitly separates itself from ledger_metrics_list by scoping to workspaces with few or no metrics, so an agent can tell what it returns without opening a 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?

Gives three explicit triggering conditions ('few or no metrics', 'someone asks what they should be measuring', 'a decision needs a number to settle against and none exists') and names the downstream tool (ledger_metric_presets_adopt). It even steers the output behavior — suggest 3-6, not the whole catalog.

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