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oddly commerce corpus

Audit a public storefront

store_audit

Run oddly's free storefront audit against a public ecommerce domain and return the findings: detected platform, the checks that failed, and how the store's catalogue compares to observed category norms where the corpus can say. Reads the store's own public pages only, obeys robots.txt, and is rate limited. Use the bare domain (example.com). Never pass an internal host or an IP address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe storefront domain or URL to audit, e.g. 'example.com'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does so well: it discloses reads of public pages only, robots.txt compliance, rate limiting, and the shape of the result. It stops short of the full profile (no mention of failure modes when the domain is unreachable, or whether results are cached).

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?

Three front-loaded sentences: purpose and output first, then behavioral guarantees, then input constraints. Every sentence earns its place except a bit of promotional framing ('oddly's free'), which is minor noise.

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

Completeness5/5

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

For a single-parameter tool with no annotations and no output schema, the description covers the purpose, the return content, the safety/etiquette profile (robots.txt, rate limit, public-only), and the input format. Nothing an agent needs in order to call it correctly is missing.

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 100% so the baseline is 3, but the description adds real meaning: the accepted input must be a bare public domain and must not be an internal host or IP. That constraint goes beyond the schema's example and directly shapes how the agent formats the argument.

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 states a specific verb+resource ('Run oddly's free storefront audit against a public ecommerce domain') and enumerates the returned findings (platform, failed checks, catalogue comparison). This is clearly distinguishable from the sibling benchmark_* tools without opening any schema.

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

Usage Guidelines4/5

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

It gives explicit input-shape rules — 'Use the bare domain (example.com)' and 'Never pass an internal host or an IP address' — which is strong when-not guidance for the parameter. It does not, however, name the sibling tools or say when to prefer them over this audit, so it falls short of a 5.

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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