hmc_processed_metrics

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

Given readOnlyHint=true, the annotation already conveys safety, but the description adds substantial behavioral context: it details what each mode returns, mentions the empty `{}` result for fetch, specifies ISO-8601 UTC timestamps and ~2h retention, and lists the key structure of links output. This goes beyond the annotation and helps the agent anticipate edge cases.

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?

The description is a well-organized paragraph that leads with an action-oriented summary, then provides essential context and mode details. No sentence is redundant; every part adds useful information, and it remains concise given the tool's complexity.

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?

The description covers the main behaviors: listing, fetching, required parameters, timezone/retention, and the empty result case. It is slightly incomplete in that `end_ts` and `no_of_samples` are not explicitly described, and there is no mention of pagination or limits, but the presence of an output schema mitigates the need to describe return values.

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 0% schema description coverage, the description is the only source of parameter meaning. It clearly explains `category`, `resource_name_or_uuid`, `start_ts`, and `mode` with examples and default behavior. However, `end_ts` and `no_of_samples` are not explicitly defined—only implied by 'requested range'—leaving a gap for those parameters.

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?

The description opens with 'List or download processed PCM metrics JSON documents,' a specific verb-resource combination that clearly identifies the tool's function. The context about 30s granularity and ~2h retention further distinguishes it from siblings like hmc_aggregated_metrics, even though no explicit alternative is named.

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?

The description explains the purpose of the tool and the modes ('links' vs 'fetch'), which implies when to use it (when processed metrics are needed). However, it does not explicitly compare with alternative tools such as hmc_aggregated_metrics or provide exclusion criteria, so the guidance is inferred rather than explicit.

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