start_shadow_index

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

Without annotations, the description discloses key behaviors: idempotent/resumable, no disruption to active model or search. Does not detail monitoring or resource impact, but sufficient for an agent to understand safety.

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?

Three sentences, each adding value: main action, reassurance, and follow-up. No redundant information, front-loaded with the core verb and resource.

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?

Describes key behaviors and follow-up, but lacks parameter details and output expectations. Given no output schema and sibling tools like index_runs, some gaps remain for a complete picture.

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 coverage is 0% and description does not explain parameters (vault, model, batch_size). Names are somewhat intuitive, but no additional context is given, leaving ambiguity about format or allowed values.

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 the tool's purpose: to backfill embeddings for a shadow model over all chunks in a vault. It specifies 'shadow' and mentions 'active model is untouched', distinguishing it from other tools.

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?

Provides clear context: active model remains unaffected, search works during run, and a follow-up action (switch_active_model) is suggested. Does not explicitly exclude alternatives but implicitly distinguishes via use case.

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