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Plan a rules-checked East End day

plan_my_day

Build a complete East End day using Hamptons Verified's deterministic planner. Use this whenever someone asks ChatGPT or Claude to plan, schedule, sequence, or personalize a day—not search_places, which returns an unordered list. The tool produces three distinct options and applies the same constraints as the website before returning anything: permanent closures, the selected date and opening hour, age fit, budget, weather, daylight, geographic sequencing and the maximum drive between consecutive stops. saved_places is a preference lane: pass names the asker supplies and eligible ones are worked into the day, but they never override a safety or feasibility rule; the rest of the stops remain discoveries. This connector cannot read the asker's private Hamptons Verified account, browser or saved list, so ask for the names when they want them included. Present the returned plan; never replace a stop from your own memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
whoNo
dateNoISO date in East End local time; defaults to today.
seedNoOptional stable seed when the asker wants the same result repeated.
townNoA hamlet or region to keep the day around. Omit for the full East End.
vibesNoComma-separated interests such as quiet, foodie, cultural, beach, adventure, romantic, active, or off-season.
budgetNo
energyNo
saved_placesNoComma-separated saved venue names supplied by the asker. Never infer private account data.

TDQS

A4.5/5.0
Behavior4/5

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 key behavioral details: determinism, three returned options, enforced constraints like closures and weather, saved_places as a non-overridable preference lane, and the connector's inability to access private account data. It does not describe the returned format in detail, but the core behavior is well covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but not bloated; each sentence adds either scope, usage guidance, or behavioral context. A few of the constraint lists could have been trimmed, but overall the structure is well organized and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 8 params, no required fields, and no output schema, the description covers the essential functional and behavioral context: when to use the tool, how saved_places works, what constraints are applied, what to return, and how to handle missing private data. It does not detail the output plan structure, but it is sufficient to use without major opaque gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 63%, so the description adds meaningful value beyond the schema. It explains that saved_places is a 'preference lane' and that eligible names never override safety or feasibility rules, and it clarifies that no private saved-list data is accessible.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific action: 'Build a complete East End day using Hamptons Verified's deterministic planner.' It clearly names the resource, the output type, and explicitly differentiates it from search_places, which is a sibling tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says to use this tool 'whenever someone asks ChatGPT or Claude to plan, schedule, sequence, or personalize a day' and warns against search_places, which returns an unordered list. This is strong when-to-use and when-not-to-use guidance.

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

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TDQS

A4.3/5.0
Disambiguation4/5

Most tools target a distinct domain, and the descriptions explicitly cross-reference each other (e.g., beach_info vs parking_permit_rules). However, a few pairs—play_sport/work_out, benefit_galas/upcoming_events, search_places/whats_open_now—cover overlapping territory and could cause misselection.

Naming Consistency2/5

Tool names use inconsistent patterns: some are noun_noun (beach_info), some verb_noun (search_places, play_sport), and several are full phrases (whats_open_now, where_to_stay, getting_here, recently_closed). This makes the naming unpredictable despite consistent snake_case.

Tool Count4/5

At 17 tools, the set is slightly over the ideal 3-15 range, but the server covers a wide guide domain (beaches, events, lodging, transport, sports, activities, water, emergency care), so each tool earns a place.

Completeness4/5

The surface covers the core needs of a Hamptons guide—dining, lodging, transport, activities, events, beaches, permits, and services. Minor gaps exist (e.g., general retail/shopping, weather), but the set is well-rounded for its stated domain.

Resources