Massive Context MCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it's a retrieval tool ('Get'), which implies read-only behavior, but doesn't clarify permissions, error handling (e.g., what happens if the index is invalid), or performance aspects. While it hints at a workflow ('after chunking'), it lacks details on data persistence or side effects. This is inadequate for a tool with no annotation coverage.

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 appropriately sized and front-loaded: the first sentence states the purpose clearly, and the second provides usage context. The parameter explanations are brief but relevant. There's no wasted text, though it could be slightly more structured (e.g., bullet points). Overall, it's efficient and earns its place.

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 has an output schema (which handles return values), 2 parameters with 0% schema coverage, and no annotations, the description is moderately complete. It covers purpose, basic usage, and parameter meanings, but lacks behavioral details like error handling or performance. For a retrieval tool with output schema, this is adequate but has clear gaps in transparency and parameter elaboration.

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 description adds minimal parameter semantics: it explains 'name' as a 'Context identifier' and 'chunk_index' as 'Index of chunk to retrieve.' With 0% schema description coverage, the schema provides no details, so the description compensates slightly by giving basic meanings. However, it doesn't elaborate on format (e.g., string constraints for 'name' or integer range for 'chunk_index'), leaving gaps. Baseline is 3 as it adds some value but doesn't fully compensate for the coverage gap.

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's purpose: 'Get a specific chunk by index.' It specifies the verb ('Get') and resource ('chunk'), and distinguishes it from siblings like 'rlm_chunk_context' or 'rlm_list_contexts' by focusing on retrieval by index. However, it doesn't explicitly differentiate from 'rlm_get_results' or 'rlm_inspect_context', which might also involve retrieval, so it's not a perfect 5.

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 provides some usage guidance with 'Use after chunking to retrieve individual pieces,' which implies a prerequisite (chunking must be done first) and context. However, it doesn't explicitly state when to use this tool versus alternatives like 'rlm_get_results' or 'rlm_inspect_context', nor does it specify exclusions. This leaves room for ambiguity in sibling tool selection.

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