Salsmart — Israeli Grocery Prices

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

The annotations already declare read-only, idempotent, non-destructive, and closed-world behavior, so the description does not need to repeat safety. It adds real operational context by defining freshness as a successful fetch within 12 hours and a source file published within 72 hours, and it flags that there is no live-stock guarantee.

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?

It leads with the return content, then defines the freshness thresholds, then qualifies the limitation. Every sentence carries actionable information and there is no filler.

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?

An output schema exists, so the description need not enumerate return fields. With no parameters and annotations covering safety, the description is nearly complete, though it could briefly clarify what branch coverage means or when a stale result should trigger a fallback.

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?

The tool takes zero parameters, so the schema-description burden is minimal. The baseline for zero parameters applies, and there are no missing parameter semantics to compensate for.

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?

The description states a specific verb-and-resource: it returns covered branches and the freshness of their retailer price files. That is clear enough for an agent to know what it gets back, though it does not explicitly contrast itself with the sibling tool search_products.

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 is implied by the title and the freshness definition, so an agent can infer this is a pre-check tool. However, the description never says when to call it versus search_products, nor does it give any exclusions or prerequisites.

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

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

Adds real behavioral context beyond the annotations: result cap of 20, inclusion of retailer source, fetch times and citation URLs, no-cost usage with shared fair-use limits, and the fact that stock/payments are out of scope. The fetch-time disclosure is especially valuable for freshness judgment; missing only guidance on what an empty or truncated result means.

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?

Three tight sentences, front-loaded with what is searched and what comes back, then cost limits, then exclusions. Nearly every clause earns its place; the free/fair-use note could be marginally tighter but is genuinely useful.

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?

Output schema exists, so return structure needn't be explained, and the description still usefully signals the 20-item cap and citation URLs. Scope exclusions round it out; only result-truncation or empty-result behavior is left implicit.

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 description coverage is 100%, so both q and limit are already documented, including the leading-zero barcode tip. The description restates the query forms and implies the 20-result cap but adds no syntax or formatting detail beyond the schema, so the 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?

States a specific verb and resource ('Search actual branch-level grocery prices') plus the accepted query forms (Hebrew/English name, manufacturer, barcode). This is specific enough that an agent can distinguish it from the only sibling, get_data_status, without opening a schema.

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?

Gives clear positive context (search by product name, manufacturer, or barcode) and explicit exclusions ('Does not check live stock or take payments'), which steers the agent away from misusing it. It stops short of naming an alternative tool or stating prerequisites, so a 4 rather than a 5.

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