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

With no annotations, the description carries the full burden and does so: it discloses persistence semantics, the exact receipt contents, the two status values (intent_recorded vs demand_logged) and their condition, the failure mode (recording_unavailable, no ticket issued), a concrete rate gate (100/caller/day, 5,000 service-wide), no auth requirement, and a secrecy warning for the poll URL.

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?

About 200 words, but front-loaded with the core action and receipt contract, and every clause (rate gate, privacy warning, open-door no-op) adds operationally useful information. The Industry Leader exception is the one piece that arguably belongs earlier, since it changes whether the call does anything at all.

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?

For a 7-parameter mutation tool with no output schema and no annotations, the description fully compensates: it enumerates the return payload, the status values, the error path, rate limits, and the no-op case. An agent has everything needed to decide whether to call and how to interpret the result.

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%, so the schema already documents all seven parameters including enumerations and lengths. The description adds only light context — that the notify registration is how you learn about re-census changes and that the intent joins the brand-visible aggregate — without explaining parameter formats or interactions beyond the schema. Baseline 3 applies.

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?

Specific verb + resource ('Register intent at a brand's Outpost: declare what you came to do') with the key precondition stated up front — the brand's door is walled for that intent. It also distinguishes this from pre-check tools by describing the walled-door case and noting that at Industry Leaders the call records nothing and returns a door_open pointer, so an agent can tell what this call actually accomplishes.

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?

Usage context is clear: call it when the door is walled for your intent, and at Industry Leader brands (peetscoffee, kroger, bestbuy) the call is a no-op returning a door_open pointer. It stops short of explicitly telling the agent to call get_outpost_door_state or list_outposts first, leaving the pre-check routing to inference.

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