LebTech - electronics prices in Lebanon

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

Annotations already establish readOnlyHint=true and openWorldHint=false, lowering the bar. The description usefully adds in-stock-only filtering, Lebanon geography, a 10-result cap, and heuristic ranking for laptops, but says nothing about sort exclusivity (is it strictly ascending price?), tie-breaking, or empty-result behavior.

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?

Two short sentences with the core purpose front-loaded and no filler. The parenthetical aside is slightly awkward but does add ranking context rather than padding.

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?

For a read-only, single-category filter tool with no output schema, the description covers stock status, geography, result cap, and optional filters. Only minor gaps remain around exact ordering semantics and return contents, which are low-stakes here.

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 only 25%, so the description must compensate. It loosely maps all four parameters: 'budget' to max_price_usd, 'brand' to brand, 'up to 10 results' to limit, and category via the enumerated scope. Still, it gives no format details for max_price_usd (USD? filters cheap-but-above-budget items?) beyond the passing mention.

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 (find the cheapest) and resource (in-stock products in a category), so the agent can distinguish it from search_products or get_product_prices. The parenthetical about laptops ('cheapest among sensible, new machines first') is somewhat cryptic but still signals category-specific ranking logic.

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 through scoping phrases like 'currently in stock', 'optional budget and brand', and 'up to 10 results', which hint at when the tool fits. However, it never explicitly contrasts itself with the sibling tools get_product_prices, price_history, or search_products, leaving the agent to infer the boundary.

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?

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), and the description adds real behavioral context: prices are live, results are restricted to shops holding the identical configuration rather than any similar model, and rows are sorted cheapest first with deep links. It doesn't address what happens when no shop stocks the item, but the added context is substantive.

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?

Two sentences, front-loaded with the resource and scope, then the input contract. Every clause carries information (scope, ordering, link inclusion, accepted input forms) with 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?

For a one-parameter tool with no output schema, the description usefully sketches the return shape (per-shop rows, sorted, linked) and the matching constraint. It leaves the zero-results case and URL/id edge cases unstated, a minor gap given the low complexity.

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 coverage is 100% and the single parameter's description already enumerates the accepted id and /product/ or /laptop/ URL forms. The description restates exactly the same accepted formats, adding no syntax, validation, or example beyond the schema.

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 resource ('live per-shop prices') with an explicit scope ('for ONE product in Lebanon') and even the ordering ('cheapest first'). That scoping immediately separates it from category-level tools like cheapest_in_category and from search_products, without needing to name them.

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?

The description implies when to use it (you have one product and want shop-by-shop prices) and tells you what input it accepts, but it never explicitly says when not to use it or which sibling to pick instead (e.g. search_products to obtain an id, price_history for trends). Usage is inferable rather than stated.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description adds genuinely new context: the ~90-day tracking window and the exact shape of what is reported (current low, period low/high, drop since tracking began, weekly lows). With no output schema, this disclosure is doing real work; it stops short of notes on data freshness, missing products, or coverage limits.

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?

Two sentences, front-loaded with scope and followed by input forms; every clause carries information and there is no filler. The first sentence is dense but still readable.

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?

For a single-parameter read tool with safety annotations, the description covers both the query scope and the returned fields, which compensates for the absent output schema. It lacks only edge-case behavior (unknown ids, no history yet, non-Lebanese products), which is minor here.

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?

Only one parameter with 100% schema description coverage, so the schema already carries the accepted input forms. The description restates the same id//product///laptop/ URL formats, adding no syntax, normalization, or error-handling detail beyond the schema.

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 resource and scope: the lowest price of ONE product across Lebanese shops over ~90 days, plus the exact aggregates returned. This separates it from search_products and cheapest_in_category by implication, but it never names a sibling or explicitly rules them out.

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 scope ('one product', 'last ~90 days', historical aggregates) rather than stated. There is no explicit when-to-use, when-not-to-use, or pointer to get_product_prices for current prices, leaving routing to the agent's inference.

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?

With readOnlyHint=true and openWorldHint=false already covering the safety profile, the description still earns credit for disclosing data freshness (re-checked nightly), result ordering (most widely sold first), a hard result cap (up to 10), and the laptop-only nested model_page behavior. It does not cover auth needs or what happens on zero matches, which keeps it short of a 5.

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 with no filler: purpose and scope first, then return shape and ordering, then the laptop-specific nuance. Information-dense without being padded. Slightly crowded but front-loaded correctly.

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?

With no output schema, the description steps in to describe the returned shape (products, lowest price, shop count, page link) and the model_page expansion, which is exactly what an agent needs before calling. Minor gaps remain: the effect of the limit parameter and behavior on empty results are unstated.

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 75%, so the schema already documents query, category and max_price_usd, establishing the baseline of 3. 'Returns up to 10 products' loosely relates to the limit parameter's maximum of 10 but does not explain the parameter's role, and the description adds nothing about category enum values or how max_price_usd interacts with the returned lowest price.

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 gives a specific verb and resource ('Find electronics sold in Lebanon and their live prices across Lebanese shops') plus clear scope (USD, nightly re-check). An agent can tell this is a keyword-search-over-catalog tool. However, it never names or contrasts the siblings (cheapest_in_category, get_product_prices, price_history), so the boundary with get_product_prices in particular is left to inference.

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?

There is no explicit when-to-use or when-not-to-use guidance, and none of the three sibling tools are mentioned. The agent must infer usage purely from the verb 'Find' and the sibling names. No exclusions or routing conditions are provided.

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