rlm_get_chunk

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

No annotations are provided, so the description must disclose behavioral traits. The description implies it is a read operation ('Get'), but does not explicitly state lack of side effects, permissions, or other behaviors. It is adequate but could be more explicit.

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 extremely concise: one sentence plus a two-line args list. It is front-loaded with the purpose and contains no filler.

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 two parameters and an output schema (not shown), the description is complete. It explains the tool's purpose and parameter meanings. The output schema presumably covers return values, so no further explanation needed.

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?

With 0% schema description coverage, the description adds meaning by documenting parameters: 'name: Context identifier' and 'chunk_index: Index of chunk to retrieve.' This clarifies purpose beyond the raw 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 'Get a specific chunk by index' and provides context 'Use after chunking to retrieve individual pieces.' It distinguishes itself from sibling tools like rlm_chunk_context (likely creates chunks) and rlm_get_results (likely gets results).

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 after chunking to retrieve individual pieces,' indicating when to use it. Although it does not mention when not to use it or alternatives, the guidance is sufficient for a simple retrieval tool.

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