PriceInIndia

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds useful behavioral context beyond that: the result carries ids and slugs (the identifiers needed downstream) and the tool is a discovery entry point rather than a search. It doesn't discuss ordering or whether the taxonomy is fixed/complete, but that is minor for a zero-param listing.

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, zero waste. The purpose is front-loaded and the workflow hint follows immediately after.

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 zero-parameter, read-only listing with an output schema and full annotation coverage, the description supplies exactly what remains: what the tool is for and how it chains into the next tool. Nothing an agent needs 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes no parameters, so there is nothing to document; baseline for zero params is 4. The mention of ids and slugs refers to output, not inputs, and is harmless.

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?

Specific verb + resource: 'List the product categories available on PriceInIndia (India), with ids and slugs.' It also implicitly distinguishes itself from siblings by positioning itself as the discovery step that precedes list_category_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?

Explicitly states when to use it ('Use this to discover categories') and names the follow-up tool and its required input ('then call list_category_products with a slug'). This is a complete routing instruction, leaving nothing to 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?

Annotations already declare readOnlyHint, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds an important behavioral caveat: it returns the cheapest listing per store for the query, not necessarily the identical SKU, which prevents incorrect assumptions about exact-product comparison.

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?

The description is three tight sentences: primary behavior first, then the key caveat, then workflow guidance. Every sentence adds useful information and nothing is wasted.

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?

Given the annotations, full schema coverage, and an output schema, the description provides everything needed: scope, return shape, a critical semantic caveat, and integration guidance with sibling tools.

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 parameters (query and brand) are already documented in the schema. The description reinforces that this is a product-query tool but adds no further syntax or usage detail for the brand filter, so baseline 3 is appropriate.

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 ("Compare prices"), names the retailer scope, and specifies the return shape: cheapest listing per retailer sorted by price. It also distinguishes itself from search_products by saying it can be used after search or standalone, so the agent can identify its role without opening the 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?

It explicitly gives workflow guidance: "Use after search_products or standalone; then render_product_results to display the offers as cards." This tells the agent both preceding and following tools, making invocation sequencing clear.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds genuine value beyond that by disclosing the required calling sequence (slug lookup before listing, rendering after). It stops short of noting pagination limits (max page 20) or behavior on an invalid slug, so not 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 short sentences, each doing distinct work: what it does, how to get the required input, what to do with the output. Front-loaded with the core action and 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 return values need no explanation, and annotations cover safety; the description completes the picture with the prerequisite and follow-up steps. Minor gap: it doesn't mention that results are paginated or that page is capped at 20, which an agent managing multi-page retrieval would want to know.

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%, so the baseline is 3. The description goes beyond the schema by supplying multiple example slugs ('camera', 'laptops', 'mobile-phones') and, more importantly, naming browse_categories as the authoritative source for the required slug. It says nothing about the optional page or sort parameters, which the schema already covers.

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'), resource ('products'), and scope ('in a PriceInIndia category (India)') with a concrete slug example. An agent can distinguish it from search_products and browse_categories 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.

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

Explicitly sequences the workflow: 'Use browse_categories first to find the right slug' and 'Then render_product_results to display the products as cards.' It names both the prerequisite sibling and the follow-up sibling with the condition that selects each.

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, destructiveHint=false, openWorldHint=false, so safety is covered. The description adds value beyond that by disclosing the rendering effect in the chat ('interactive product cards') and the immutability constraint on the payload. It does not mention the 20-item cap or what happens if validation fails, so it is not fully exhaustive.

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 short sentences, front-loaded with what the tool produces before the prerequisite and the constraint. No filler or restatement of the title.

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 an output schema present, the return shape needs no explanation, and annotations cover the safety profile. The description supplies the one thing structured fields cannot: that this must follow a retrieval call and must receive unmodified data.

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%, so the baseline is 3; the nested product fields, currency const, and item limits are all documented in the schema. The description's only addition is the 'pass through unchanged' constraint, which the schema already states for the products array, so it adds little new semantic information.

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 ('Display') plus resource ('selected products') and the output form ('interactive product cards in the chat'), which cleanly separates it from the retrieval siblings. An agent can tell this is a terminal rendering step, not a search step, without opening the 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?

Explicitly names the prerequisite tools (search_products, compare_prices, list_category_products) that must run first, and states the data-integrity rule ('Do not invent or modify product data'). The ordering constraint and the pass-through requirement leave nothing to 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?

Annotations already cover read-only, non-destructive and closed-world, so the safety profile is settled; the description adds substantive context about the payload (price, MRP, discount, store, image, links plus brand/store/category/price-bucket facets). It omits pagination limits and result-cap behavior, which it leaves to the schema.

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?

Front-loaded with purpose and scope, then returns, then the workflow. The final sentence chains three separate instructions, which is efficient but slightly run-on; nothing in it is 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?

With an output schema present, the description need not enumerate return values, yet it still gives a useful preview and fully documents the call sequence. The only gap is practical calling detail around paging through results and how the category filter connects to browse_categories, which is only implied via the schema.

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%, so all nine parameters including the sort enum and page/per_page bounds are already documented. The description adds only the India-retailer scope and does not explain filtering interactions (e.g., how brand/store/price filters relate to facets), 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 + resource ('Search PriceInIndia for products sold in India') and scopes the result set (aggregated listings from Amazon, Flipkart, Croma, Reliance Digital). An agent can immediately distinguish it from compare_prices and render_product_results, which the description names as downstream steps.

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?

Explicitly says 'Call this first for any product question', then prescribes the optional follow-ups: compare_prices for cheapest-per-retailer and render_product_results for card rendering. The ordering and the role of each sibling are stated rather than inferred.

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