artifact_storage_bloat_analysis

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

The description marks the tool as [READ] and describes its output, indicating non-destructive operation. However, no annotations are provided, so the description carries full burden. It does not disclose potential performance impact, authentication needs, or rate limits, but the read-only nature is clear.

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 structured with a clear header, body explaining functionality, an Args section, and a Returns section. It is front-loaded with the purpose but could be slightly more concise; still, every sentence adds value.

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?

Given no output schema and 0% schema coverage, the description provides a thorough explanation of the tool's behavior, parameters, and return value. It covers the essential aspects for an agent to use it correctly, though it omits error cases.

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?

The description explains all 5 parameters: old_artifact_days, limit, projects, artifacts_by_project, and target, including their defaults and purposes. This adds significant value beyond the schema, which has 0% description coverage.

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 clearly states it ranks projects by storage and estimates reclaimable artifact bytes, using specific verbs 'rank' and 'estimate'. It distinguishes from sibling tools like list_artifacts (which only lists artifacts) by focusing on analysis and reclaimability estimation.

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?

It explains when to use it: for storage bloat analysis, either by providing pre-existing data or pulling live from a target. It does not explicitly exclude alternatives, but the context implies this is for analysis before deletion or cleanup.

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