prc_gate

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 transparently describes the precondition (must present checkpoint context first), valid decisions and their consequences (approve/proceed, reject/revise, question/pause), and the follow-up actions. It does not detail internal state mutations, but for a gate tool this level of disclosure is strong, though not perfect.

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 concise yet information-dense, organized with an action statement, a critical usage warning, checkpoint enumeration, decision meanings, and post-action behavior. Every sentence earns its place, with no fluff or redundancy, and the most important constraint is front-loaded.

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?

Despite having no output schema and no annotations, the description is fully self-contained for a gate tool: it names the three checkpoints, explains valid decisions and their downstream effects (including linking to prc_synthesize after Checkpoint 3), and references the current Pre-RC research stage, which situates it within the broader workflow. It leaves no obvious questions about when or how to use it.

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 coverage is 100% (all three parameters have descriptions), so the baseline is 3. The description adds meaningful semantics beyond the schema by explaining what each decision entails ('approve' means proceed, 'reject' means revise with feedback, 'question' means pause for clarification) and how these map to workflow steps. This is richer than the schema's simple string examples.

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 action ('Submit a checkpoint decision') and resource ('current Pre-RC research stage'), and delineates the three checkpoints (Checkpoint 1, 2, 3) with their specific contexts. This distinguishes it from sibling tools like 'rc_gate' or 'postrc_gate' by explicitly anchoring it to the Pre-RC research stage.

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 explicit usage directives: 'NEVER call without presenting the checkpoint context to the user first and getting their explicit decision' and explains exactly what to do after each decision type ('After approve: proceed to next stage or prc_synthesize... After reject: re-run the relevant stage with user feedback'). This gives clear when-to-use and when-not-to-use guidance, exceeding the baseline.

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