deep_storage_purge

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

No annotations provided, but description fully discloses conditions: never touches entries without compressed blobs, default/minimum thresholds, safety notes on accuracy and unaffected search tiers, and reclaim percentage.

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?

Well-structured with sections, bold key terms, and no superfluous sentences. Every sentence adds value, including safety and usage guidance.

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?

Despite no output schema, description explains expected behavior, preview with dry_run, and impact on storage and search. Covers all needed context for an agent to invoke 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 covers all 3 parameters (100%), and description adds context: default values, minimum enforcement, dry_run behavior, and project filter omission meaning. Adds significant meaning beyond schema.

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?

Description clearly states the tool purges high-precision float32 embedding vectors for entries with TurboQuant compressed blobs, specifying the exact resource and action. It distinguishes from siblings by focusing on post-backfill space reclamation.

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 states when to use: after TurboQuant backfill (session_backfill_embeddings). Also mentions dry_run for previewing impact, giving clear context for safe execution.

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