rag_ingest

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

With no annotations, the description carries the burden, and it does well: it discloses that ingestion is a long-running background operation, returns a task ID, and may return immediate results. This gives meaningful context beyond the tool name, though it doesn't touch on failure or cancellation behavior.

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 compact and well-structured with a clear purpose statement, Args section, and Returns section. Every sentence earns its place; no fluff.

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?

For a long-running operation with one optional parameter and no output schema, the description covers the essential aspects: process, duration, and return value. It could note how to track the task (e.g., via cancel_task or get_task_status), but overall it is sufficiently complete.

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%, but the Args section fully explains source_name: its purpose, an example, its default (None), and what happens if omitted (all configured sources). This is complete compensation for the bare 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?

The description opens with 'Full crawl and index of documentation sources' and details the pipeline: crawl GitHub repos, fetch docs, chunk, index for semantic search. This clearly distinguishes it from siblings like rag_search, rag_update, and rag_status.

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 optional source_name behavior and notes this is a long-running background operation, implying use for full ingestion. However, it does not explicitly contrast with rag_update or state when to use this tool versus alternatives.

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