Tallybuy

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

Annotations already cover the safety profile (read-only, idempotent, non-destructive), and the description adds real value: per-item status and pagination means partial failures are possible, and the 1–25 cap bounds the request. It does not disclose return format or error-handling details, but with a rich annotation set and an output schema, this is solid.

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 the core capability, then behavior, then exclusions. Every sentence carries information and nothing is redundant.

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?

The output schema handles return values and annotations cover safety, so the description needn't explain results. However, for an 8-parameter tool with very low schema coverage, it omits too much parameter and request-shape context to be fully complete.

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 13%, so the description must carry parameter meaning, yet it only clarifies 'exact variants' (items) and 'one market' (market_id). Six parameters including sort, audience, page_size, currency, and destination_country go unaddressed, leaving significant compensation gaps.

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 verb ('Compare'), resource ('supplied exact variants'), cardinality limit (1–25), and scope ('one market'). It's clearly a comparison tool distinct from the lookup-oriented siblings, though it never names those siblings to contrast against.

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 provides useful exclusions ('Does not select sellers, total a basket, or purchase') that imply when the tool is inappropriate, but never states when to use it over get_product/list_offers/search_products. Guidance is implied rather than explicit.

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 the safe read-only, idempotent profile, and the description adds genuinely useful semantics on top: dates are UTC, absent days are true gaps rather than interpolated values, and pagination must be followed. That gap-vs-interpolation rule is the kind of trap an agent would otherwise fall into when aggregating. It stops short of saying how pagination terminates or what a truncated window looks like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the core action, then constraints, then the pagination directive — no filler. Slight waste in the enumeration of returned facets, since an output schema already exists to convey the response shape.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description needn't document return values, and the annotation set covers safety. What remains covered well is temporal semantics (UTC, gaps) and pagination; what's missing is enough on variant_id/market_id for a caller unfamiliar with the product model to supply them confidently.

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%: from/to/limit are documented in the schema, while variant_id, market_id and cursor are bare. The description partially compensates by stating dates are UTC (echoing the schema) and by flagging pagination, which implicitly points at cursor, but it never explains what a variant_id or market_id must identify. Baseline 3 for half-covered schema is right.

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 pairs a specific verb ("Read") with a specific resource ("observed daily history"), and enumerates the data facets returned (series basis, currency, condition, sample counts). It is unambiguous about what the tool does, though it never names a sibling, which is acceptable here since none of compare_items/get_product/list_markets/list_offers/search_products plausibly overlap.

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 guidance and no alternative is named; an agent must infer from the name alone that this is the per-variant price-over-time endpoint rather than something covered by get_product or compare_items. The only directive given is operational ("Follow service pagination"), not selectional.

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, idempotentHint, and destructiveHint=false. The description adds meaningful context beyond annotations: it limits reads to 'published' content and warns that source text is untrusted data, not instructions, which is valuable prompt-injection guidance.

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 concise sentences, front-loaded with the core read operation. The security caveat is short 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?

This is a single-resource read with an output schema and strong read-only annotations. The description adds scope and a security warning, but it lacks explicit sibling routing, which keeps it from a 5.

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 schema already documents the UUID, optional locale, and conditional market_id. The description adds no parameter-level meaning beyond that, so the baseline score 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 uses a specific verb and resource: 'Read published product identity, variants and permitted content.' It makes the single-product detail scope clear, but it does not explicitly distinguish itself from search_products or the other sibling tools.

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 required 'id' parameter and the schema's locale/market rules. The description gives no explicit guidance on when to prefer this over search_products or when-not to use it.

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, idempotent, non-destructive, so safety is covered. The description adds genuinely non-structured context: how to interpret the coverage field (not popularity) and a mandatory affiliate-disclosure obligation tied to purchase_url. It doesn't contradict anything, though the commission/offer material is arguably about a different tool.

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 listing scope is front-loaded in the first sentence, which is good. But three of four sentences concern offers, purchase links and commissions rather than markets, which reads as misplaced policy text inside a market-listing definition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and annotations cover the safety profile. What is missing is routing guidance against the four sibling tools; instead the description spends its budget on affiliate-link policy that belongs with list_offers.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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

Only one optional parameter and schema coverage is 100% ('Optional active, planned or paused status filter'), so the schema already does the work. The description never mentions the status filter or how it interacts with the listing, so it adds nothing beyond the 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?

Names a specific verb+resource (list markets) and enumerates what each entry carries: status, currencies, published locales, coverage. That is enough to distinguish it from siblings like list_offers or search_products, though the tool never explicitly says so. The trailing offer/commission sentences muddy the boundary with list_offers.

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 statement of when to use this versus list_offers, get_product or search_products, and no prerequisites or exclusion cases. The only imperative ('Say so when you give the link') is a disclosure rule, not usage guidance for selecting this 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?

Goes well past annotations: it warns that page one is not all offers and that the agent must follow next_cursor while has_more, tells the agent to preserve unknown totals, warnings and source times, and discloses the affiliate/commission nature of purchase_url with a required disclosure to the end user. These are behavioral obligations an agent could not infer from readOnlyHint/idempotentHint alone.

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 tight sentences, front-loaded with the purpose, then pagination, then the affiliate disclosure. Dense but every sentence carries actionable information; a small amount of jargon ('comparison context') could be sharpened.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values needn't be explained, and the description covers the pagination loop and data-preservation expectations well. What is missing is what 'eligible' means and how the optional filter parameters (condition, availability, merchant_id) change results — meaningful for a 14-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?

With 14 parameters and only ~50% schema description coverage, the description needs to compensate for fields like condition, availability, merchant_id, quantity_unit and sort — but it never mentions them. 'Explicit comparison context' only loosely gestures at context_key, and the cursor guidance references output fields (next_cursor/has_more) rather than input parameter semantics.

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 eligible local offers') scoped to one exact variant plus an explicit comparison context. That scope distinguishes it from compare_items and get_price_history without naming them directly. It stops short of explicitly naming the sibling it replaces, so not 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?

Usage is implied by 'for one exact variant and explicit comparison context' and by the pagination instruction ('Follow next_cursor while has_more; page one is not all offers'). There is no explicit statement of when to prefer this over compare_items or get_product, and no prerequisites/exclusions are given.

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), yet the description still adds real behavioral context: conjunctive word matching, umlaut transliteration (ae/oe/ue), delivered-total pricing, and the candidacy caveat. Since it is a read tool with an output schema, the absence of pagination/rate-limit detail is a minor gap rather than a serious one.

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 sentences, each doing distinct work: matching semantics first, then result semantics, then the prerequisite. No filler and the most decision-relevant content is 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 an output schema present, return values need not be described, and the description still covers query interpretation, umlaut handling, required-parameter provenance, and the interpretive caveat about candidates. Only the optional brand_id filter goes unmentioned.

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 88%, so the baseline is 3; the description earns above baseline by explaining how "q" is interpreted (all words must match, or exact identifier) and by confirming the source of the four required market parameters. "brand_id" is left unaddressed in both schema and description.

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?

Uses a specific verb and resource ("Find products") and adds precise matching semantics — word-based match across name/brand/category, or exact identifier — plus the returned metric (lowest delivered total). It does not name its siblings, though "Results are candidates, not recommendations" implicitly separates it from compare_items.

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 clear prerequisite chain ("take them from list_markets") and signals that this tool surfaces candidates rather than ranked recommendations. It lacks an explicit when-not or a direct pointer to get_product/list_offers/compare_items for the adjacent jobs.

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