submit_project_creation_preflight_feedback

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

With no annotations provided, the description carries the full burden. It discloses that the tool is 'append-only' and that the data is a 'preference signal' not to be treated as factual proof or authority. This gives useful behavioral context, though it doesn't mention persistence, side effects, or error behavior.

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 and front-loaded with the primary action. Each sentence adds meaningful guidance, and the structure flows logically from purpose to usage constraints to data characterization. It could be slightly tighter by removing the 'neutral episode' phrase, but overall it's efficient.

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 annotations and an opaque schema, the description covers the key aspects: what the tool does, how to use it, when to set a particular flag, and the nature of the data. It omits details about return values or error handling, but the presence of an output schema reduces the need for that. It's fairly complete for the given complexity.

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 schema has no parameter descriptions, so the description must compensate. It does so by instructing to pass the complete JSON from preflight (implied receipt_json) and by referring to 'all three judgments' (likely helpfulness, factual_grounding, calibrated_criticality). It also explains the confirm_user_feedback flag. However, it doesn't explicitly map each field or explain idempotency_key, leaving some residual 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 clearly states the tool's purpose: to record a user's judgments for a preflight receipt. It references the specific source tool (preflight_project_creation) and distinguishes it from sibling tools by focusing on feedback submission. However, the phrase 'neutral episode' is somewhat ambiguous, preventing a perfect score.

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 clear usage instructions: pass the complete JSON from preflight_project_creation, set confirm_user_feedback only after explicit user feedback, and never infer feedback from other actions. It implies this tool is for the feedback step in the preflight pipeline, but it doesn't explicitly contrast it with refine or create steps, which would be clearer.

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