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

Annotations already cover the safety profile (readOnlyHint, destructiveHint=false, openWorldHint=false), so the description only needs to add context — which it does: sort order ('busiest first'), the 14-day window for trace counts, and the shape of the payload. It omits pagination/limits and auth expectations, keeping it just short of a 5.

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 the resource definition and packed with useful detail in two sentences. Density is high and the nested em-dash clauses ask for careful reading, but no sentence is wasted.

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?

No output schema exists, so the description carries the burden of describing returns — and it does, enumerating source name, ingestion method, per-day trace counts, and top tools with shares. It stops short of mentioning result limits or paging, a minor gap for a list endpoint.

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?

With 100% schema coverage on a single parameter, the schema already documents the workspace slug, defaults, and API-key behavior fully; the description adds nothing about parameters. Baseline 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?

States a specific verb+resource (list Caliper sources) and immediately defines what a 'source' is — an app sending traces via its own code, OpenTelemetry, or a published Workbench flow. This clearly distinguishes it from siblings like caliper_sources_over_time, caliper_source_feeds_list, and caliper_sources_to_dataset.

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?

Explicitly says when to reach for it ('Start here when the user asks how their agent behaves on real traffic') and names the follow-on tool with its condition ('then caliper_sources_over_time for one source'). This is textbook routing guidance with an alternative named.

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