MoneyDeals – US Tech Deals

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

Annotations already declare readOnly/idempotent/non-destructive, so the description is free to add value — and it does, disclosing that marketplace offers carry labels (is_marketplace, marketplace, ships_from, delivery_days_max, shipping_cost, seller_type, store_rating). It does not say what non-marketplace entries look like or how missing/unknown ids are handled, leaving a genuine behavioral gap.

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, core capability front-loaded, and the dense field list is the only place with real informational payload. The trailing user-facing instruction ('mention ships_from and delivery time') is arguably tool-adjacent but earns its place by shaping output use.

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 the return-shape burden and partially meets it by naming the marketplace fields. It still omits the non-marketplace shape, error behavior for invalid or duplicate ids, and whether comparison is limited to same currency/market.

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 50%: market is documented inline (only 'us' supported) but ids is not. The description adds the meaning of ids ('deals by id') and restates the 4-item ceiling, which the schema already enforces via maxItems. Baseline 3 is appropriate given partial coverage.

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 ('side-by-side comparison of up to 4 deals by id') plus a hard cardinality limit, which separates it from the single-deal get_deal and the open-ended search_deals. It never names a sibling explicitly, so the differentiation is inferred rather than stated.

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 phrase 'side-by-side comparison' — you use it when you already have 2–4 known deal ids and want them together. No when-not-to-use condition or alternative tool (get_deal, search_deals) is named, and the second sentence is a presentation directive rather than selection guidance.

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 readOnly/idempotent/non-destructive, so the bar is lower; the description still adds real behavioral context the annotations cannot convey — the suggested_deals fallback when a brand has no coupons, and the distinct aliexpress response shape with min_spend and ends_at. It stops short of describing pagination or result ordering guarantees.

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 front-loaded definition and fallback behavior are efficient, but the definition then spends most of its length on a 22-item brand enumeration and an 8-category list. That coverage detail is mildly useful but reads as padding rather than decision-relevant content.

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, zero-required-parameter lookup with no output schema, the description covers scope, filters, fallback behavior, and one returned field (suggested_deals). Return shape and pagination remain unstated, but nothing needed to invoke 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?

Schema coverage is 75%, so the baseline is 3, and the description adds genuine meaning beyond the schema: brand's optionality and its special 'aliexpress' semantics, and that category is only honored when no brand is supplied. The limit parameter is never mentioned in either place, leaving one small gap.

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 names a specific resource and its two variants ('verified, currently valid US coupons (type code)' and 'code-free promotions (type promotion)'), plus the geographic scope. An agent can distinguish this from search_deals and get_deal 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 clearly states brand is optional and what happens without it (newest verified coupons, optionally category-filtered), plus the special 'aliexpress' path and the suggested_deals fallback. It routes to list_brands for the full list, but never contrasts itself with siblings like search_deals or get_deal, so the when-to-use guidance is clear but not exhaustive.

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 (readOnly, idempotent, non-destructive), and the description goes beyond them by disclosing what the response contains (condition field, marketplace labeling fields) and how to surface shipping info. It does not cover failure behavior for a bad id/URL, which keeps it below 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?

Front-loaded with the core action and lookup keys, then a parenthetical field list and a doc link. The field inventory is dense but relevant to a tool with no output schema; nothing is wasted, though the listing could be trimmed.

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 partially compensates by naming response fields (condition, is_marketplace, marketplace, ships_from, etc.), which is genuinely useful. It still omits the url-vs-deal_id contract and any error/not-found behavior, leaving gaps for a lookup tool with zero required parameters.

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 33% (just the market enum), so the description has to carry the rest; it does clarify that url is a moneydeals.com deal URL and deal_id is the deal identifier. However, with 0 required params it never says whether url or deal_id should be used, whether they are mutually exclusive, or which wins if both are supplied.

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 ('Get one deal by its id or moneydeals.com deal URL'), and the singular 'one deal' plus the identified lookup key distinguishes it from siblings like search_deals and get_coupons. An agent can select this 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 tells the agent how to identify a deal (id or URL) and even how to present results ('mention ships_from and delivery time'), but never states when to prefer this over search_deals or what to do when the deal is unknown/invalid. Usage is implied rather than routed.

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/idempotent/non-destructive, so safety is covered; the description adds real value by disclosing the return payload shape (brand + active deal count + verified coupon count) and the 155+ brand coverage scope. It omits pagination behavior, which matters because the default limit of 100 is below the stated 155+ brand coverage.

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 first sentence is front-loaded and efficient, but the description then dumps 20 example brand names and an 8-item category enumeration that adds bulk without changing how the agent calls the tool. Roughly half the text is 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?

With no output schema, the description carries the burden of describing returns and does partially (deal and coupon counts, coverage volume). However it never explains that results are paginated/capped by limit, which is the key omission given 155+ brands vs. a 100 default.

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 documents market, with_offers_only, and value ranges. The description only reinforces the category filter ('optionally filtered by category') and adds nothing about limit, market, or with_offers_only semantics, so it is baseline-adequate rather than additive.

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 ('List the brands MoneyDeals covers') and even names what the payload contains (active deal and verified coupon counts). It does not explicitly contrast itself with the closest sibling, list_categories, though 'Use list_brands for the full list' hints at the split.

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 a concrete trigger question ('Which brands do you cover?') so the agent knows the intent this tool serves. It never states when-not to use it or which sibling to prefer for filtered/brand-specific lookups, so it stops short of full routing guidance.

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, idempotent, closed-world, and non-destructive behavior. The description adds only the domain scope of the categories and no further behavioral traits such as return format, pagination, or whether the list is static.

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 front-loaded sentence with no redundant phrasing. Appropriately sized for a simple list tool.

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 low-complexity read-only list tool with full schema and annotation coverage, the description is nearly complete. The only gap is that no output schema exists and the description does not describe the returned category shape, though that is minor.

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% for the single market parameter, including an enum and default description. The description adds no parameter detail, so the baseline of 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 (List) and resource (consumer-tech categories) scoped to MoneyDeals. The resource itself differentiates it from sibling list_brands, but no sibling is named explicitly. Clear purpose with no explicit sibling routing.

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 guidance on when to use this tool versus alternatives like list_brands or search_deals. Usage is only implied by the purpose statement, with no when-to-use or when-not-to-use context.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful output context (the good-price assessment, 90-day average, lowest recorded price), but says nothing about rate limits, data freshness, or what happens for a deal with sparse history.

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 that begins with the resource and wastes no words. It is efficient, though the comparative clause is slightly dense and unpacks only on a second read.

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 does the right thing by summarizing the return payload. However, it omits where a deal_id comes from (get_deal/search_deals), gives no sibling routing, and leaves two of three parameters unexplained – gaps that matter for a tool with no documented output contract.

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 33% – only 'market' is documented, and that documentation is largely redundant with its single-value enum. The description does implicitly tie the '90-day average' to the days parameter default, which helps, but it says nothing about the required deal_id or how the days window changes the assessment.

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?

Names a specific verb+resource ('Price history for a deal') and adds the analytic angle ('Is this a good price?' vs. 90-day average and lowest recorded price), which tells the agent what it gets. It does not explicitly distinguish itself from sibling get_deal, 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 when-to-use or when-not-to-use guidance and no alternatives named, even though get_deal and compare_products appear to overlap on price data. The 'Is this a good price?' framing hints at a purchase-decision context but that is inference, not guidance.

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 (readOnly, idempotent, destructive=false), so the bar is lower, yet the description still adds real behavioral detail: the result-ranking rule (US retailers/brand stores before marketplace), the 15%-cheaper inclusion threshold for China-shipping offers, and the shape of marketplace/coupon data. It does not describe empty-result or default-limit behavior, keeping it below 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?

The purpose is front-loaded in the first sentence, followed by condition/field guidance and coverage notes, so an agent can stop reading early. The long enumerations (20 example brands, 8 categories) add search hints but are somewhat padding, slightly diluting conciseness.

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 return-value detail and does so well (condition values, marketplace labels, coupon structure). It is nearly complete for a 9-parameter read tool, but leaves several input parameters and default-limit semantics undocumented, so it falls just short of full completeness.

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 44%, so the description must compensate, and it does so only partially: it clarifies the query/category dimensions, lists the 8 category values, and mentions ships_from, but limit, max_price, min_discount, include_marketplace, retailer and market get no added meaning. Much of the field detail (is_marketplace, seller_type, store_rating, best_coupon) describes outputs, not inputs.

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) plus resource (deals) and scope (current, verified consumer-tech deals on MoneyDeals US) and enumerates the queryable dimensions (product name, model, brand, category). It also routes the agent to a sibling, naming list_brands for the full brand list, so an agent can tell it apart from at least one alternative 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?

The description gives clear context for when this is the right entry point (searching deals by name/model/brand/category) and explicitly names list_brands as the alternative for a full brand enumeration. It lacks explicit when-not guidance against the other siblings (compare_products, get_deal, price_history), so it stops short of a 5.

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