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Crawlora MCP

sevennow_deals

Read-only

Every currently discounted item in one 7NOW store, paginated, each with the promotion driving the discount.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoOptional and inert: store_id alone selects the store. 7now.com's own client sends it, but responses are byte-identical with any value, including none -- measured live 2026-09-06 across three stores. Accepted and forwarded for fidelity with the real client.
lonNoOptional and inert: store_id alone selects the store. 7now.com's own client sends it, but responses are byte-identical with any value, including none -- measured live 2026-09-06 across three stores. Accepted and forwarded for fidelity with the real client.
skipNoPagination offset. Defaults to 0.
limitNoMax items returned, 1-100. Defaults to 20.
store_idYesRequired. 7NOW store id, from GET /7now/stores.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that results are paginated and that each item carries its driving promotion, which is useful context, but it says nothing about page size defaults, rate limits, or authentication needs beyond what the schema states.

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

Conciseness5/5

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

A single front-loaded sentence that names the resource, the scoping constraint (one store), pagination, and the promotion payload with zero filler. Every clause earns its place.

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?

An output schema exists, so return-value detail is not required, and the description correctly flags pagination and the promotion-per-item shape. For a read-only, single-required-param list tool the coverage is nearly complete, with only sibling disambiguation missing.

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

Parameters3/5

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 store_id, skip, limit, and the inert lat/lon pair. The description adds no syntax or format detail beyond that, which is the expected baseline when the schema does the heavy lifting.

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

Purpose4/5

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

States a specific verb-scope and resource: 'every currently discounted item in one 7NOW store', with pagination and the promotion attached to each item. An agent can tell what it returns, but it never distinguishes itself from close siblings like sevennow_offers or sevennow_promotion, which sound like they cover the same discounted-item space.

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

Usage Guidelines2/5

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

No when-to-use, when-not-to-use, or alternative guidance is given. With sevennow_offers and sevennow_promotion present in the sibling list, the agent gets no signal about which of the three to call for a given need, leaving selection to inference.

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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