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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so safety is covered. The description usefully adds the shape of the aggregation and the meaning of latency values (p50/p95 as "answered within" bucket edges), which the annotations cannot convey. It omits any note on cost of computing 365-day windows, caching, or auth constraints beyond the schema.

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, then the metrics, then the recommended workflow. The metric enumeration is dense and the parenthetical on p95 bucket edges is slightly awkward, but each clause carries real information about the return shape rather than 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?

With no output schema, the description carries the burden of describing returns and does so thoroughly — metrics, per-tool breakdowns, share-of-traces, top documents, models — and tells the agent what to do next. Nothing essential for calling it correctly is missing.

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%, so sourceId, days (default 30, max 365) and workspace are already fully documented, putting the baseline at 3. The description adds no syntax or default information beyond the schema, though it does frame what the returned window represents.

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 and resource — reading one Caliper source day by day — and enumerates exactly what is computed (traces, failures, tool calls, tokens, cost, latency percentiles, documents, models). This distinguishes it from listing tools like caliper_sources_list and from trace-level siblings such as caliper_traces_list.

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 use case ("how often is it calling web search and is that changing") and a concrete analytic procedure (compare first/last weeks, name the day it moved), plus a follow-up route to caliper_traces_list. It does not state when NOT to use it or contrast it with a potentially overlapping analytics sibling like caliper_flow_performance.

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