source_get_content

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

With no annotations provided, the description fully discloses behavior: it returns original indexed text from various sources, mentions no AI processing, and lists return fields. Although it does not explicitly state read-only, the verb 'get' and return types strongly imply a non-destructive operation.

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 highly concise, using a single opening sentence and structured bullet points for args and returns. Every sentence adds value without redundancy, and the key purpose is front-loaded.

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 a simple API, the description covers input (source_id as UUID), output structure (content, title, source_type, char_count), source types (PDFs, web pages, etc.), and performance context (faster than notebook_query). It is complete for this tool's complexity.

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 input schema only defines source_id as a string, but the description adds that it is a 'Source UUID', providing format context. It also details all return fields and their types, adding significant meaning beyond the 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 uses the verb 'Get' and clearly identifies the resource: 'raw text content of a source'. It distinguishes from sibling tools like notebook_query by stating 'no AI processing' and being 'much faster', making its purpose specific and unique.

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 explicitly tells when to use this tool: 'Much faster than notebook_query for content export', and implies it is for retrieving raw text without AI processing, giving clear context vs alternatives.

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