rlm_execute

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions several safety mechanisms (sandbox, transactional CoW rollback, linter, governor) which imply controlled side effects and validation. However, it does not specify whether the operation is read-only or mutating, what happens on error, or the nature of side effects beyond rollback. This is a moderate level of transparency given the short description.

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 a single, dense sentence that packs multiple salient features without fluff. It is front-loaded with the primary action ('Sandboxed RLM REPL executor') and immediately conveys key behavioral characteristics. Every word contributes value.

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 tool with three parameters and no schema descriptions, the description is severely incomplete. It omits an explanation of what RLM is, what each parameter means, what the return value looks like, and under what circumstances the tool should be used. The agent would have to guess at nearly every aspect of usage.

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 no meaning to any of the three parameters (code, query, scope_paths). Since schema description coverage is 0% and the description never touches them, the agent receives no semantic context beyond the bare parameter names, which is insufficient for correct invocation.

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 identifies a specific action: executing RLM code in a REPL, and adds notable features (sandboxed, transactional CoW rollback, linter, governor). However, it does not differentiate this tool from its siblings (cpg_query, memory_evolve, swarm_blackboard) by explaining what distinguishes it or when to prefer it.

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 no guidance on when to use this tool versus its siblings. It does not state conditions, prerequisites, or explicitly mention alternatives, forcing the agent to infer usage solely from the name and generic executor label.

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