guardentry_chat

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

No annotations exist, so the description carries the burden. It discloses a key behavioral trait: write actions are queued for dashboard approval. This goes beyond the schema and provides useful safety context, though it leaves some behavior (e.g., response format) unspecified.

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?

Three short sentences, front-loaded, no fluff. Each sentence adds value: purpose, capabilities, and write-approval queuing.

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?

No output schema and no annotations, so the description should cover return values and usage boundaries. It explains capabilities and write approval but does not describe what the agent can expect in the response or when to use specific sibling tools, leaving some gaps.

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% with examples for both parameters. The description adds minimal new meaning beyond 'natural language message' and does not elaborate on conversation handling, 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 clearly states the tool sends natural language messages to GuardEntry and enumerates capabilities (query, create, generate). This distinguishes it from sibling tools like guardentry_list_risks which are structured queries.

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 implies use for general natural language interaction but does not explicitly state when to prefer this over more specific sibling tools or exclude structured actions. It provides context but no explicit when/when-not.

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