knowl_ingest

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

Annotations only include openWorldHint=true, which says nothing about side effects or safety. The description says 'process' and 'ingest' but doesn't disclose whether this mutates the knowledge base, whether it's reversible, or what happens to existing knowledge. It also doesn't mention the autoResolve behavior that could change knowledge. Given the low annotation coverage, the description should carry more behavioral detail but doesn't.

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 two sentences, front-loaded with the core purpose and a critical usage caveat. Every word earns its place; there is no fluff or repetition. It is concise and immediately actionable.

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?

With no output schema and minimal annotations, the description should clarify what the tool returns and any side effects. It doesn't mention the return value (e.g., a commit ID or status), nor does it explain how it differs from knowl_ingest_atoms. The tool likely has side effects (ingesting knowledge), so more context about consequences and the resulting state would be needed for an agent to call it confidently.

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 description coverage is 100%, so all parameters are documented in the schema. The description adds a bit of context by saying 'explicitly supplied raw source text,' which clarifies that text should be raw and explicitly given, and it implies the text param is the main input. It doesn't add meaning for autoResolve or commitMessage beyond what the schema says, so baseline 3 is appropriate.

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 states a clear purpose: 'Process explicitly supplied raw source text through the configured Knowl AI pipeline.' It specifies the resource (raw source text) and the action (process through pipeline). It doesn't name a specific sibling but distinguishes the explicit-ingestion scope, which is enough to differentiate from related tools like knowl_ingest_atoms, though that distinction is implied rather than stated.

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?

It gives a strong usage rule: 'Use only for an explicit ingestion request; never silently ingest the current conversation or prompt.' This tells the agent when to call it and when not to. It doesn't compare with alternatives like knowl_ingest_atoms, but the explicit request condition is a clear guideline that covers most usage decisions.

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