iDevice Wearables

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

Annotations cover the safety profile (readOnlyHint=true, openWorldHint=false), and the description goes beyond them by disclosing the output's provenance model (Confirmed/Reported/Our read with source outlet and date) and the cross-category comparison limitation.

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 dense sentences, front-loaded with what the tool returns before the optional filter. Every sentence carries information, though the 'same engine as idevice.com/compare' clause is the weakest.

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 still explains the shape of each result cell and its sourcing, and annotations already carry the read-only safety profile. An agent has everything needed to call and interpret it.

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, but the description adds value by giving a concrete keyword example (['battery','sleep']) that clarifies how the specs filter actually matches rows.

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 (side-by-side compare) and resource (specs for 2-3 products), and the 'from the same engine as idevice.com/compare' note plus the 2-3 product limit clearly separates it from siblings like get_product_facts and get_detailed_facts.

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?

Implies usage clearly (compare 2-3 products at once) and adds a real constraint: products in different categories are compared on shared structured facts only. It does not name an alternative or state when not to use it, 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.

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

Annotations declare readOnlyHint=true and openWorldHint=false so the safety profile is covered, but the description adds real behavioral value: the result set is restricted to on-sale items, sorted cheapest-first, and each row carries best current retailer price plus retailer and date, list price, and the verdict/Guide link. That is meaningful disclosure beyond the annotations, though it doesn't cover result volume or pagination.

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 dense but well-ordered sentences — scope, filters/ordering, then result contents, then the sibling routing. Every clause carries information; the enumeration of categories in prose is slightly redundant with the schema enum-less description, but it is front-loaded and 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?

With no output schema, the description compensates by naming the returned fields (retailer price, retailer, date, list price, verdict, Guide link). Combined with filtering, ordering, and sibling routing, an agent has everything needed to call and interpret it correctly.

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, but the description adds semantics the schema doesn't: 'at or under a price' clarifies that max_price is an inclusive ceiling, and 'from one company' clarifies the company filter matches a single brand rather than a list. These are genuine refinements, not restatements.

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 (on-sale products), the required scope (one category, with the categories enumerated), and the output ordering ('cheapest first'). It also carves out the model scope (current and previous models) and routes pre-orders elsewhere, so an agent can separate it from list_products and get_release_calendar 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?

Explicit about when this applies: on-sale items in one category, optionally narrowed by price ceiling or a single company. It also names the exclusion and the alternative explicitly — 'pre-orders and unreleased products are in get_release_calendar' — 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?

With only readOnlyHint/openWorldHint annotations, the description carries the return-value burden and does so well: it enumerates the five answer states (Works, Works with a limit, Needs extra hardware, Does not work, Not confirmed), the evidence words, and clarifies the easily-misread 'Not confirmed means unknown, never incompatible'. That is substantial behavioral context beyond the annotations.

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?

Four sentences, front-loaded with the resource and then the result semantics and parameter hint; little waste. Slightly dense enumeration of statuses but each clause carries information.

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?

No output schema exists, and the description compensates by describing the answer values, evidence categories and source link, which is what an agent needs to interpret results. Minor gap: it does not mention pagination or whether all compatibility items are returned when query is omitted.

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 the schema already documents both parameters and its query example. The description adds only a marginal nuance about narrowing to a single thing ('e.g. iphone or android'), which overlaps the schema's own example. 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 (get) and resource (compatibility) with precise scope: 'what a product works with, from its Guide's Works with tab'. The scope distinguishes it from siblings like get_product_facts, get_in_the_box and get_detailed_facts, which cover different aspects of a product.

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 content (answering compatibility questions) and the optional query parameter ('narrows to one thing'), but there is no explicit when-to-use/when-not or named alternative such as get_product_facts. An agent can infer the context but must choose between siblings on its own.

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 safety (readOnlyHint=true, openWorldHint=false), and the description adds genuinely useful context beyond them: each fact carries value, unit, attribution, and source page, and it explains that 'Confirmed' means the maker's own statement. That provenance detail materially shapes how an agent should interpret and cite results.

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?

Well front-loaded: the opening clause states the full scope before the topic enumeration. The 12-item topic list is long but earns its place by signalling valid narrowing keywords; still, it reads as a run-on sentence rather than a scannable structure.

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?

No output schema exists, and the description compensates by describing the returned fact record (value, unit, attribution, source page) and the grouping. For a simple two-parameter read tool, this is close to complete; only sibling disambiguation 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 description coverage is 100% and both parameters are documented there, including the topic example, so the baseline of 3 applies. The description reinforces that topic is an optional narrowing keyword, but adds no syntax or matching rules 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 verb and resource ('every individual fact on file for one product') and enumerates the grouping topics, so the agent knows exactly what comes back. It does not, however, distinguish itself from the closely named sibling get_product_facts (or get_product), leaving the agent to guess which one to call.

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 only usage guidance is that the optional 'topic' narrows the list. There is no statement of when to prefer this over get_product_facts, get_product, or get_compatibility, and no exclusions or prerequisites, so the agent must infer selection.

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, so the safety profile is covered. The description adds substantial context about what data is returned, including price history, release status, and a published verdict, which is valuable behavioral context for an agent deciding whether this tool supplies the needed information.

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 a single, very dense sentence that front-loads the main purpose but then strings together many clauses. It is informative but could be structured more efficiently with bullets or shorter sentences to improve readability.

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, one-parameter tool with no output schema, the description does explain the returned content well. However, it omits usage guidance relative to the many sibling tools, leaving a meaningful gap for correct tool selection.

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% for the single product_slug parameter, and the schema already provides an example. The description adds no additional meaning about parameter format, constraints, or alternatives, 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?

The description states a specific verb and resource: it retrieves the 'short summary of one product's Guide' and enumerates the fields returned. However, it does not distinguish this tool from siblings such as get_product, get_product_facts, or get_report_card, so an agent must infer the boundary from the name alone.

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 prerequisites, and no explicit comparison to alternatives in a crowded sibling set. The implied use case is retrieving a product summary, but the description never states when this tool is preferable to get_product or get_detailed_facts.

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, so the safety profile is covered. The description goes further by disclosing data provenance and interpretation rules ('as the maker's own page states it', 'false means the maker says it is not'), which is genuinely useful for deciding how much to trust a missing item.

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 a colon-enumerated payload list; every clause carries information and nothing is repeated. It is dense but not wasteful.

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 correctly carries the burden of describing the return shape (item, quantity, included flag, source page). It omits edge behavior such as empty results or how multiple models are ordered, which is a minor gap.

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 are already documented; the description only restates that variant narrows results to one configuration, adding little beyond the schema's 'Part of a configuration name, e.g. Pro'. 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?

The description names a precise resource and scope: what ships in the box for one product, broken out per model or configuration, with the source page. An agent can distinguish it from siblings like get_product_facts or get_detailed_facts because the returned artifact is explicitly the packing list.

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: 'Optional variant narrows to one configuration' tells the agent the variant is an optional filter, but there is no when-to-use/when-not guidance and no routing to or away from any sibling tool.

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 and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: it discloses which data is aggregated (lowest retailer price over 30/90-day windows) and, importantly, that bundles and refurbs are 'marked and left out of the range' — a filtering behavior an agent could not infer from annotations.

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 dense sentence, appropriately front-loaded with the resource before the detail clauses. Every clause carries information, though the long parenthetical listing return fields makes it slightly harder to parse than an explicitly split sentence would be.

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?

No output schema exists, so the description must carry return-shape information, and it does describe the returned data (first/last observation, range, the points themselves, bundle/refurb handling). Minor gaps remain — currency/units and whether the 30/90-day windows are relative to now — but the definition is largely complete for a simple read 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?

With a single parameter at 100% schema description coverage, the schema already documents product_slug with an example. The description adds nothing about slug format or sourcing beyond what the schema provides, 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 resource (dated price history for one product) with concrete scope: lowest retailer price in the last 30 and 90 days plus the full researched observation history. This clearly distinguishes it from siblings like get_product, compare_products, and get_release_history, which an agent can rule out without opening schemas.

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. The description never mentions compare_products as the alternative for multi-product price comparison, nor does it state any precondition (e.g., that a slug from list_products/search is needed). Usage is only inferable from the resource name.

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 cover the safety profile (readOnlyHint=true, openWorldHint=false), and with no output schema the description usefully discloses the shape of the response — lifecycle, price with official/estimated distinction, availability basis, report count and sourcing quality. It also flags the empty-report case. It omits nothing critical, but adds no auth, rate-limit, or staleness 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?

One dense noun-phrase sentence that front-loads the most important fields (lifecycle, price, dates, availability) and ends with the edge-case note. No filler, though the comma-separated field list is slightly heavy to parse.

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 compensates by enumerating the returned fields, and the sole input is documented in the schema. Given the tool's modest complexity, an agent has enough to call it correctly; only sibling disambiguation 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?

There is a single parameter, product_slug, and schema description coverage is 100%, so the schema already carries the burden. The description adds no format or example detail beyond what the schema provides, which is the expected baseline here.

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 resource (one product) and enumerates what status means: lifecycle, price, key dates, availability, report count and sourcing quality. That is a clear verb+resource, though it never names the sibling tools (get_product_facts, get_price_history, get_reports) that overlap with these same fields, so an agent must infer which one 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?

Usage is only implied: the natural read is 'call this for a single product's summary.' The one explicit guideline is the edge case 'Works for products with no reports yet,' which is genuinely useful, but there is no statement of when to prefer this over get_product_facts or get_price_history.

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 only cover the safety profile (readOnlyHint=true, openWorldHint=false), so the description's disclosure of data provenance carries real weight: prices are 'official' only when announced or on sale and otherwise labelled an estimate, availability carries 'the last price we read' (a staleness signal), and every spec is tagged Confirmed/Reported/Our read/No source with outlet and date. It stops short of stating what an unknown slug returns or whether fields can be absent, but the reliability semantics are unusually rich.

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 dense sentence-fragment with zero filler, front-loading price — the field an agent most likely needs — before dates, availability, compatibility, and specs. Nothing is repeated from the schema or annotations.

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 usefully stands in for one by enumerating the returned fields and their confidence labels, which is the main gap it needed to close for a read-only, one-parameter tool. It is only slightly incomplete on error/empty-result behaviour.

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?

With one parameter at 100% schema description coverage, the schema already documents product_slug and gives an example, so the baseline is 3. The description adds no format, resolution, or lookup semantics beyond that.

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 enumerates the concrete payload — official/estimated price, announcement and availability dates with source, availability and where to buy, compatibility summary, and specs — so the agent knows exactly what resource this returns. However, it never contrasts itself with the overlapping siblings get_product, get_detailed_facts, get_compatibility, get_in_the_box, or get_price_history, so disambiguation 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 statement, no exclusions, and no named alternative despite a crowded sibling set with obvious overlap (get_product, get_detailed_facts, get_price_history). The only implicit signal is the content list, which hints at scope but does not route the agent between tools.

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 and openWorldHint already given, the description still adds real behavioral context: the taxonomy of date sources (Announced by the company, Company event, Reported date, Reported window, iDevice estimate), the one-year maximum window, and the non-obvious rule that products with no dated or sourced window are counted rather than listed. That last rule materially affects how an agent interprets a short result set.

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 dense sentences, front-loaded with what is returned before the filtering and edge-case rules. The parenthetical source list is long but carries information an agent needs to interpret results; nothing reads as 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?

There is no output schema and only minimal annotations, so the description correctly carries the burden of explaining return contents and edge behavior, which it does well. The remaining gap is sibling differentiation against get_release_history, which would make selection unambiguous in a twelve-tool namespace.

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, but the description adds genuine meaning: it restates the default window (120 days) and its relationship to from/to, reinforces the one-year ceiling, and enumerates the category vocabulary inline. This is more than a restatement of the schema text.

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 precise verb-and-resource: products not yet on sale, ordered by date, with the source of each date and a pre-release report count. It is unambiguous what the tool returns, but it never distinguishes itself from the obvious sibling get_release_history (past vs. future releases), 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?

Usage is implied through scope statements — 'Defaults to the next 120 days' and optional from/to/category/company narrow it — which tells the agent when the tool applies but not when to prefer it. No alternative (e.g. get_release_history) is named, and no exclusion is stated for already-released products.

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, covering the safety profile, and the description does not contradict them. Beyond that, it usefully discloses the shape of the returned payload (dates, sources, launch price, and gap statistics in days and months), which matters given there is no output 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?

A single dense sentence that leads with the resource and enumerates contents economically. It is appropriately sized for the tool's scope, though the clause structure is slightly compressed rather than crisply front-loaded.

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 one required parameter, no output schema, and simple annotations, the description covers what the agent needs to call the tool and roughly what it returns. The main omission is usage/routing guidance relative to 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?

There is a single parameter with 100% schema description coverage, so the schema fully documents product_slug including an example ('apple-watch'). The description adds no further parameter meaning, which is the expected baseline.

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 resource (every generation of a product's line with announcement/release dates, sources, launch price) and the derived stats (gaps: mean, median, shortest, longest). It's clearly a read/retrieval tool, but it never explicitly contrasts itself with siblings like get_price_history or get_product, leaving differentiation implicit.

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 exclusions, and no mention of alternatives such as get_price_history or get_product. The agent must infer when this tool is preferable purely from the return content described.

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, so safety is covered, and the description adds real value on top by disclosing the return shape: the outcome-category roll-up, the per-record fields, and newest-first ordering. It still says nothing about result limits or pagination, 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?

Two sentences, tightly packed, with the roll-up purpose front-loaded and query behavior trailing. Dense but every clause carries content; the long enumerated parenthetical is justified by the actual enum-like categories.

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 correctly carries the return-value burden and does so by listing the record fields and ordering. It is nearly complete for a read-only retrieval tool, missing only pagination/limits and sibling routing.

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, but the description clarifies the scope of `query` beyond the schema: it matches words in the summary OR the outlet, which the schema's generic 'Words to look for in the records' does not specify. That is genuine added meaning.

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 with clear scope: a roll-up of one product's pre-release reports plus the underlying records. The enumerated outcome buckets (Right, Partly right, Wrong, etc.) make the content unmistakable. However it never names or distinguishes itself from close siblings like get_reports or search_reports.

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: an agent can infer this is the tool for a per-product report card, and the optional query's narrowing effect is noted. There is no when-to-use/when-not guidance and no routing to the obvious alternatives get_reports or search_reports.

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 and openWorldHint=false, so safety is covered; the description adds real context by disclosing that only 'well-sourced' reports are returned and enumerating the return fields and the full set of seven status values. It omits pagination/ordering behavior, 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?

One dense sentence, front-loaded with the resource and scope, and the status enumeration earns its length by telling the agent exactly what statuses to expect. Slightly heavy on commas but no filler sentences.

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 correctly carries the burden of describing the return shape (status, outlet count, first reporter, evidence link), which is the right thing to include. It could still say whether the result set is paginated or ordered, but it is largely complete for a read-only lookup.

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 only two parameters, so the schema already documents product_slug and the category filter. The description adds no syntax, format, or example detail beyond what the schema provides, so 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 ('Every well-sourced pre-release report for one product') with clear scope. However, it never differentiates itself from siblings like search_reports, get_reviews, or get_release_history, so an agent must infer the boundary from the name alone.

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 'Every ... for one product' implies this is the exhaustive per-product retrieval, which hints at usage, but there is no explicit when-to-use statement and no mention of the closely related search_reports alternative for filtered lookups.

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/openWorldHint already covering the safety profile, the description adds real behavioral context: the consensus is normalized and only surfaces after three scored reviews, and it discloses data provenance (the scores are the outlets' work, not iDevice's testing). It omits pagination or return-shape details, but the additions are 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?

Everything is packed into two sentences with the core resource front-loaded and the provenance caveat trailing. No filler, though the first sentence is dense enough that the enumeration of returned fields slightly blurs the purpose statement.

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, no-output-schema tool, the description does the necessary job of describing what comes back (consensus, themes, per-review outlet/rating/link) and the meaningful threshold rule. Only minor operational details are absent, which is acceptable 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?

There is a single parameter with 100% schema description coverage, so the schema already documents product_slug and its example format. The description adds no syntax or constraint detail beyond that, which is the expected baseline when the schema does the work.

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 (reviews for one product) and enumerates its content: Review Consensus, agreed themes, and each review with outlet, rating and link. It is clearly distinguishable from data tools like get_product_facts, but never contrasts itself with any sibling by name.

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 statement, no prerequisites, and no alternative tool named (e.g., compare_products for cross-product comparison). The reader must infer usage from the listed return content.

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 a safe read (readOnlyHint=true, openWorldHint=false), and the description adds genuinely useful context beyond them: the lifecycle enum values, the fact that a product may have zero reports, and the presence of product_slug. It does not address pagination or ordering, but the annotation bar is met.

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 the tool returns before the optional filter. No filler, and each clause carries information an agent needs.

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 work of describing the returned fields (lifecycle, report count, slug), which is appropriate. It leaves ordering and pagination unstated, a minor gap for a list endpoint that claims 'every product'.

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 parameter is already documented there. The description's 'filters by name, e.g. iphone 18 pro' largely restates the schema example ('galaxy ring'), adding only mild confirmation that matching is on name words.

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 ('Every product iDevice tracks') plus the shape of each entry (lifecycle, report count, product_slug), which cleanly separates it from the singular get_product and the comparison-oriented compare_products sibling.

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: enumerate all tracked products, optionally narrowing by name. It never states when to prefer get_product, compare_products, or search_reports, and gives no 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 and openWorldHint=false, so the safety profile is covered. The description adds that each result carries status and product lifecycle, which is useful return context, but says nothing about ranking, pagination beyond the schema's limit, or what 'well-sourced' actually 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?

Two sentences, front-loaded with the core action and scope, then the return payload. The examples earn their place by clarifying the keyword style, though the description largely restates the title frame.

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 should carry more of the return-shape burden; it offers only 'status and product lifecycle'. Core call mechanics are covered via the schema, but result ranking, empty-result behavior, and the meaning of 'well-sourced' are left unaddressed.

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 both 'query' and 'limit' documented (including default/max for limit). The description's example keywords ('battery', 'display', 'price') add mild practical flavor but no new syntax or constraint information, 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?

The description gives a specific verb (find/search) plus a specific resource (pre-release reports) and scope (across every tracked product), with concrete example keywords. It stops short of differentiating itself from the sibling get_reports, which sounds adjacent, so an agent cannot fully disambiguate the two from text alone.

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?

Keyword-based search across all products implies the usage context (broad discovery rather than per-product retrieval), but no alternative is named and no when-not-to-use condition is stated. An agent must infer that get_reports is the per-product counterpart.

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