BowlPrice

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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description adds genuine context beyond that: figures derive from BowlPrice's own sampling of each brand's quote process, carry a last-verified date, and include links back to BowlPrice pages — enough for an agent to judge freshness and provenance.

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 what the tool returns before the provenance caveat. Slight redundancy — 'BowlPrice tracks' and 'BowlPrice's sampling' / 'BowlPrice's page' repeat the brand name three times — but nothing is padded.

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 must carry the return-value burden, and it does: unit costs, time horizons, ranking, verification dates, and per-brand links. It does not indicate result volume or whether brands with unavailable quotes are omitted, which is a minor remaining gap for a list-returning 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 description coverage is 100%, with enums and defaults documented in the schema itself (age bands, activity levels, neutering, weight range 2–60 kg). The description only reinforces the 'one dog' framing and does not add syntax or interaction details beyond the schema, 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?

The description names the concrete output (cost per day, per month, first year), the exact population (every UK fresh and subscription dog food brand BowlPrice tracks), and the ordering (cheapest first). That is a specific resource and scope an agent can match a request against. It stops short of naming the sibling get_dog_food_price_history, so differentiation is left implicit (current cost comparison vs. historical pricing).

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 through scope constraints — 'for one dog', 'UK fresh and subscription', 'ranked cheapest first'. There is no explicit statement of when to reach for this instead of get_dog_food_price_history, and no note on when the result would be inappropriate (e.g. non-UK brands, raw/DIY feeding).

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, idempotentHint and destructiveHint already carrying the safety profile, the description adds real scope information beyond the annotations: the dataset spans five named dog sizes and includes both price changes and offer changes, which tells the agent what granularity of data it gets back. Gaps remain — no mention of how far back history goes or how large a response is — 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?

The returned-data scope is front-loaded in the first sentence, which is the right ordering, and two sentences is appropriately sized for a single-parameter tool. However, the second sentence repeats the schema's enum list word-for-word, which is dead weight in the description.

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 one-parameter read tool with no output schema and rich annotations, the description supplies the essential missing piece — what the response contains and at what granularity. It would be fully complete with a note on history depth and on how it differs from compare_dog_food_costs, but nothing critical is absent.

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% and the single brand parameter already enumerates the five ids with human-readable labels; the description's brand list is a verbatim repetition of that. It adds no new meaning such as what happens with an unknown brand or whether a default exists, 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 definition names a specific resource — every dated price BowlPrice has recorded for one brand — and specifies coverage (five sizes, price and offer changes). It is clear what the tool returns, but it never mentions the sibling compare_dog_food_costs, so the agent must infer the boundary between 'history for one brand' and 'cost comparison' itself.

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 phrase 'every dated price ... with each recorded price change and offer change' signals this is the historical-trend tool, but there is no explicit when-to-use statement, no exclusion, and no pointer to compare_dog_food_costs for the comparison case. An agent could plausibly pick either tool without guidance from this text.

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