rlm_get_chunk

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

No annotations are provided, so the description carries full burden. It states 'retrieve full content' but does not specify what 'full content' includes (e.g., text, metadata) nor potential limitations (e.g., size limits, authentication needs). Adequate but lacks some behavioral details.

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?

Two sentences, no extraneous information. Every sentence adds value: first states the function, second provides usage context and benefit. Very concise.

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 simple retrieval tool with one parameter and no output schema, the description covers the essential what and how. It lacks explicit error handling or format details, but is largely complete given the tool's simplicity.

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% and the parameter description in the schema is already clear. The tool description repeats the same info without adding new semantics. Baseline 3 is appropriate as the description adds no significant value 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 clearly states the tool retrieves full content by chunk ID, using a specific verb and resource. It also specifically differentiates from siblings by referencing the rlm_context_query pattern, making the tool's distinct role clear.

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?

Explicitly instructs to use with rlm_context_query(return_references=True) and explains the pass-by-reference pattern reduces hallucination, providing both when-to-use and the benefit. Implicitly tells when not to use (without chunk ID).

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