DiscountHub - Deals & Promo Codes

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds a genuinely useful interpretive caveat ("does NOT certify identical products") but says nothing about what the comparison returns or how the two result sets are related, leaving the behavioral story thin.

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?

A single compact sentence with the core action front-loaded and the caveat placed second. It is efficient, though verbosity is not the failure mode here – under-specification is.

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 four parameters, 50% schema coverage, no output schema, and no explanation of what a comparison yields (similarity, price delta, matched offers), an agent cannot predict the result shape or how country/max_price apply to both queries. For a non-trivial comparison tool the description leaves too much unspecified.

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 only 50%: country and max_price carry descriptions, but the two REQUIRED parameters query_a and query_b have no schema description, and the tool description does not compensate by explaining what a "search" string should contain. The description adds no parameter meaning at all.

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: "Compare two searches using real catalogue results." This is distinguishable from search_deals and get_best_deals by the two-query comparison framing, though it never names a sibling to sharpen the boundary.

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 only implied by the verb and the caveat; the description never states when an agent should reach for compare_deals rather than running two search_deals calls, nor any prerequisites or exclusions beyond the disclaimer.

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 read-only, non-destructive, open-world behavior, so the bar is lower. The description adds two useful behavioral facts beyond the schema: only active coupon entries are returned, and checkout acceptance depends on merchant conditions, warning the agent not to treat results as universally redeemable.

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?

A single compact sentence that front-loads the tool's function and appends the key caveat after a semicolon. No waste.

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 five optional search parameters and no output schema, the description is adequate for safety and purpose but thin on usage context. It does not explain how filters combine, what an empty-argument call returns, or when to prefer this over sibling discovery 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%, with every parameter documented including query, store, country, page, and limit. The description adds no parameter meaning beyond the schema, so the 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?

States a specific verb and resource: 'Find active coupon entries in DiscountHub.' This clearly separates it from deal-oriented siblings like search_deals or get_best_deals, though it does not explicitly name an alternative or explain scope limits.

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 when-to-use guidance, no mention of alternatives such as search_deals or get_store_offers, and no prerequisites. The description merely states what the tool does plus a domain caveat.

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 establish readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so safety is covered. The description adds a genuinely useful interpretation caveat — ranking by discount is not a quality/value guarantee — but says nothing about result format, pagination behavior, or how ranking ties are handled.

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?

A single front-loaded sentence with the ranking rule first and the caveat second; zero filler. Brevity is appropriate for a definition whose parameters are fully schema-documented.

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 8 optional parameters, no output schema, and an open-world data source, an agent would benefit from knowing how multiple filters interact and what a result record looks like. Annotations and full schema coverage carry most of the load, but the description leaves these behavioral questions unanswered.

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% across all 8 parameters, so the schema already documents page, limit, query, store, country, category, max_price, and min_discount. The description adds no parameter-level meaning (e.g., how filters combine), 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 (find) and resource (deals) plus the ranking criterion (percentage discount), which distinguishes it from a plain search. It does not name any sibling (search_deals, compare_deals) to sharpen the boundary, so it falls short of a 5.

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 guidance on when to choose this over search_deals, compare_deals, or get_store_offers, and no mention of prerequisites or filter-combination behavior. Usage must be inferred entirely from the name and ranking phrase.

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=true, so the safety profile is covered. The description adds essentially nothing beyond that — no note on behavior when an ID is not found, no indication of what the response contains, and 'via DiscountHub API' is filler rather than behavioral context.

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?

A single front-loaded sentence with no padding; the resource and the exact-ID constraint come first. The trailing 'via DiscountHub API' is mildly redundant but costs almost nothing.

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 two-parameter read tool with no output schema and no per-parameter schema descriptions, the description covers the core lookup intent but omits return shape, not-found behavior, and the allowed kind values. Minimum viable, with clear gaps an agent would otherwise have to discover by trial.

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 0% for two required parameters, so the description must compensate. It partially does: 'deal or promotion' maps to the kind parameter (schema constrains it to deals|promotions) and 'exact ID' clarifies that offer_id is a precise match, not a partial search. However, it never states the valid kind values or the ID format/length constraint.

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 (look up) and resource (a deal or promotion) with the key scoping qualifier 'by its exact ID,' which distinguishes it from fuzzy siblings like search_deals. It stops short of explicitly naming which sibling to use instead, so it is clear but not fully differentiated.

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 phrase 'by its exact ID' implies this is the tool to use when a precise identifier is already known, but there is no explicit when-to-use/when-not guidance and no alternative named (e.g., search_deals for name-based lookup). Usage must be inferred.

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 readOnly, non-destructive, open-world behavior. The description usefully adds that the tool reports partial failures rather than aborting, which is a real behavioral trait not in the annotations, but it says nothing about auth, rate limits, or how partial failures are surfaced.

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?

A single tight sentence with the resource front-loaded and no filler. The trailing 'reporting partial failures' clause is slightly abrupt but still earns its place by conveying failure semantics.

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 carries more burden but only covers scope and partial-failure behavior. It does not explain the response shape, the two collections returned, or that pagination applies per collection, leaving gaps for a 4-parameter tool.

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 75% and the schema already describes page, limit, and country. The description only implies the 'store' parameter via 'named merchant' and hints at per-collection paging through 'both...discounts and promotions' (matching limit's 'per collection' note), but adds no format or syntax 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 clear verb ('Find') and resource ('product discounts and promotions at a named merchant'), and the merchant-scoping distinguishes it from broader siblings like search_deals or get_best_deals. It stops short of naming any sibling explicitly, so an agent must infer the boundary.

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, when-not-to-use, or alternative routing. The agent can infer that this is the store-scoped lookup, but nothing tells it why to pick this over search_deals, find_promo_codes, or get_best_deals.

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=true, so the safety and scope profile is covered. The description adds only that the facets are 'canonical' and 'live', hinting at authoritative, freshly sourced data rather than a cached snapshot, but says nothing about what the listing contains or how it behaves.

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?

One short sentence with the verb and resource front-loaded and no redundancy. The phrase 'canonical live deal facets' is slightly opaque for the space it consumes, keeping it just short of a 5.

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 no-required-param list tool with annotations covering safety and no output schema, this is minimally viable. It omits what a 'category' is, how country scoping changes results, and how the returned categories are meant to be consumed by 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% and the single country parameter is fully documented in the schema with pattern and example ('Two-letter country code, e.g. US or UZ'). The description adds no filtering semantics, so the baseline 3 for schema-carried meaning 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 (List) and resource (categories) sourced from 'canonical live deal facets', which is distinct from siblings that all deal with deals/stores/offers/promos. The qualifier 'canonical live deal facets' is jargon but does signal the data source, and no explicit sibling contrast is drawn.

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?

No when-to-use guidance, no exclusions, no mention of alternatives such as search_deals or get_best_deals that might also surface category-like data. An agent must infer that this is the entry point for obtaining category values.

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, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds nothing behavioral beyond that: no pagination, no result-size limits, and no explanation of what the two named data sources ('canonical deal facets' vs 'promotion store directory') contribute or whether they can diverge.

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?

A single front-loaded sentence with the verb and resource first, so it is efficient and not padded. The wordy internal source phrase costs it a bit of crispness but the sentence still earns its place.

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 listing tool with no output schema, the description should at least indicate what a returned store looks like or how results are scoped/limited. It mentions two data sources without explaining their relationship or limits, leaving the agent unable to predict output or coverage.

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 optional 'country' parameter with 100% schema description coverage including a pattern and example, so the schema fully carries parameter meaning. The description adds no syntax, default, or behavior detail beyond what the schema already provides, which matches the baseline of 3.

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 clear verb (List) and resource (stores), so the basic purpose is legible. However, the qualifier 'from canonical deal facets and promotion store directory' is internal jargon that does not help an agent distinguish this from the sibling get_store_offers, which also returns store-related data.

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 guidance on when to call list_stores versus get_store_offers, search_deals, or get_best_deals. The agent must infer usage purely from the name and the vague source phrase, with no stated 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety and openness profile is covered. The description adds nothing beyond that — no note on result freshness, pagination limits, rate limits, or the fact that all filters are optional and defaults apply. It largely restates what the schema and annotations already convey.

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?

A single tight sentence that front-loads the verb and resource with no filler or repetition. It is efficient, though the sentence is arguably too thin for an 8-parameter search tool rather than overly long.

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?

Eight parameters, all optional with defaults, and no output schema. The description does not explain what happens when no query is supplied, how the default min_discount=1 and limit=5 shape results, or how paging behaves. For a tool with zero required parameters, this leaves the agent guessing at the default search behavior.

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 every one of the 8 parameters is already documented (query, store, country, category, max_price, min_discount, page, limit). The description's phrase 'using keywords and filters' adds no syntax, format, or interaction detail (e.g. how query interacts with category or store) 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 (Search) and resource (real product deals) plus the scope (across DiscountHub merchants) and the mechanism (keywords and filters). It is clear what the tool does, but it draws no boundary against siblings like get_best_deals, compare_deals, or get_store_offers, so an agent cannot tell from the description alone which of these to pick.

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 when-to-use guidance and no mention of alternatives. The seven siblings overlap heavily with a keyword-plus-filter deal search, and nothing in the description says when this tool is preferred over get_best_deals, compare_deals, or find_promo_codes. Usage is only implied by the word 'Search'.

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