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

Annotations already mark this as a safe read, yet the description adds substantial behavior the agent could not infer: status semantics (active, not_seen meaning not proof of removal, removed meaning two separate reads missed it), sinceOrEarlier semantics, date formats (YYYY-MM-DD or YYYY-MM), the enrichment caveat, and the error condition for unknown domains. Cost/metering behavior is also disclosed, which directly affects whether an agent should call it.

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?

Dense single paragraph, front-loaded with purpose and grouping before the status/date semantics. Every sentence carries information (status meanings, date formats, enrichment caveat, metering), though the run-on structure across semicolons and em-dashes makes it slightly harder to scan than an itemized form would be.

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?

No output schema exists, but the description adequately conveys the return shape: technologies grouped by category, each with status, first-seen and last-seen values, plus the store plan. Combined with error and metering notes, an agent has everything needed to decide and call correctly.

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?

There is a single parameter with 100% schema description coverage, so the schema already documents the domain format and automatic normalization. The description only restates that the lookup is by domain and adds no syntax or format detail beyond the schema. Baseline 3 is appropriate when the schema does the work.

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?

States a specific verb (list) and resource (detected technology/app stack) scoped to a single store by domain, with the grouping (by category) and the Shopify plan included. It is clearly distinguishable from siblings like get_store or get_store_ads, which cover different data about the same store.

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?

Makes the usage context explicit: one store per call, by domain, errors on unknown domains, and metered like get_store (once per store per month). It also clarifies the enriched:false case (HTTP Archive public crawl data). It stops short of naming a sibling alternative for related needs, but no exclusion is needed here since siblings answer different questions.

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