ask_cloud_llm

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 covers the redaction-first behavior, the policy decision, and the possible statuses (sent, blocked, needs_approval) along with the re-hydration behavior. It does not describe every edge case or auth requirement, but for a one-parameter send operation it reveals the consequential behavior well.

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 compact, front-loaded, and free of filler. Every sentence contributes behavior: sending, redaction, policy decision, and status handling. The formatting of status values and the confirm_send pointer is efficient and easy to parse.

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 one parameter, no output schema, and no annotations, the description does enough by explaining the three possible statuses and the follow-up path via confirm_send. It lacks explicit return-shape details, but that is mitigated by the status enumeration. It is slightly incomplete in not mentioning when redact_preview would be a better first step, but it remains sufficiently usable.

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?

There is one required parameter, text, and schema description coverage is 0%, so the description must add meaning. It does tell the agent that the text is sent and redacted first, which gives some semantic context beyond 'Text'. However, it does not describe constraints like length, encoding, or what kind of text is acceptable, leaving room for ambiguity.

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 states a specific action ('Send text to the cloud LLM through the privacy gateway') and clearly distinguishes the tool from the siblings: it is the actual send path, not redact_preview, not confirm_send, and not get_audit_log. It also names the key statuses that characterize what the tool does.

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 gives clear situational context: the text is redacted first, then a deterministic policy decides the outcome. It points the agent to confirm_send for the needs_approval case, which helps route to a sibling. It does not explicitly discuss when redact_preview should be used or when not to call this tool, but the main alternative is at least mentioned.

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