get_validation_grounding

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is 'descriptive, receipt-backed, never predictions' and 'Degrades honestly per scope', which sets expectations about output nature. It also explains the medium omission behavior and the offer_text semantics, which are behavioral traits. However, it doesn't detail what happens on missing data or error conditions, but the key behavioral aspects are covered.

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 paragraph, but it's packed with information. It front-loads the core purpose and then lists the key attributes. It's not overly long given the complexity of the tool. However, it could be slightly more structured with bullet points, but the prose is efficient and every sentence adds 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?

Given the tool's complexity (9 parameters, no output schema, no annotations), the description does a good job of explaining what the tool returns (pattern facts, survivor rates, temporal class, etc.) and how to use it. It doesn't explain the return format, but since there's no output schema, that's a gap. However, the description is quite complete for the agent to understand when and how to invoke it. It could mention what happens if the draft signature is missing, but overall it's solid.

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%, so the schema already documents all 9 parameters. The description adds value by explaining the overall conditioning ('Pass the draft's signature') and clarifying the medium parameter's default behavior and the offer_text's three-state semantics. It also explains the purpose of draft_text ('enables 'analyzed ads like this draft''). This goes beyond the schema's individual descriptions, so it earns a 4.

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: it provides time-aware NormsPack for pre-export reality check, scoped and windowed pattern facts with specific attributes. It distinguishes itself from siblings by emphasizing 'pre-export reality check' and 'draft_comparisons', which is unique among the listed tools. The verb 'get' plus the resource 'validation_grounding' is specific and the description elaborates on what the pack contains.

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 explicitly says 'Pass the draft's signature so the pack is conditioned on THIS draft' and explains the medium parameter's effect ('Omitting this treats the draft as motion...'). It also clarifies the offer_text parameter semantics ('Send an EMPTY string to mean... omit the field entirely to mean...'). This provides clear when-to-use and how-to-use guidance, though it doesn't explicitly name alternatives, the context is clear enough.

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