ingest_source

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

With no annotations provided, the description carries full burden. It discloses that for URLs it fetches page content and extracts text, and for text it saves directly. However, it does not cover potential errors, idempotency, or what 'draft card' entails (e.g., whether it's editable). This is adequate but not comprehensive.

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 concise, front-loaded with the core action, and uses clear bullet-like statements for URL vs text behavior. Every sentence adds value with no redundancy.

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 the tool's complexity (4 parameters, simple types, output schema exists), the description covers the main use cases and key behaviors. It could mention error handling or the draft card concept more explicitly, but overall it is sufficient for an agent to use the tool 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 coverage is 100% (all 4 parameters described). The description adds value by explaining the behavioral difference between URL and text input, and emphasizing the language constraint for Chinese text ('MUST be in Chinese'). This goes beyond the schema descriptions for 'source' and 'language', making parameter semantics clearer.

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 ingests a URL or raw text into the knowledge base as a draft card, with specific behaviors for each type. It distinguishes from sibling tools like fetch_url (which only fetches) and save_research (which likely expects structured JSON) by emphasizing 'without requiring structured JSON'.

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 says 'Use this when you want to add external documents, articles, or notes to the knowledge base without requiring structured JSON,' providing clear context. It implies not to use for structured data but does not name specific alternatives, leaving some ambiguity.

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