Rent-a-Skip UK skip hire

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so safety is covered. On top of that the description discloses the return shape (town page URL, county, county hub URL) despite there being no output schema, and notes that booking happens by phone with a vetted local operator. It does not say what is returned when a town is NOT covered, which is the one real 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 tight sentences, with the core purpose and return values front-loaded. The trailing booking-by-phone sentence is slightly tangential but earns some credit as workflow context.

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-only lookup with no output schema, the description covers input form, outputs and the downstream booking path. The missing piece is negative-result behavior (not covered), a minor but real omission.

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's own description already explains 'A UK town name or Rent-a-Skip town slug' with examples. The description's 'by name or slug' repeats rather than extends that, so baseline 3 is correct.

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 (checks) plus resource (town coverage for Rent-a-Skip) and even enumerates the returned values: town page URL, county, and county hub URL. Siblings (get_skip_prices, recommend_skip_size, get_permit_info) cover entirely different concerns, so an agent can route here unambiguously.

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 infers this is the coverage pre-check before booking. There is no explicit when-to-use or when-not-to-use statement, and no sibling is named as an alternative for adjacent questions (e.g. pricing or size).

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds meaningful non-schema context: the result carries a last-verified date and a data-confidence indicator, warning the agent the data may be stale or partial.

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 returned data, then the identifier rule, then the exclusion. Three sentences, no filler. The returned-field list is dense but each item is informative rather than 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?

There is no output schema, so the description usefully enumerates what comes back (fee, period, notice, renewal, link, freshness, confidence) and how to identify the council. Coverage is good; it does not mention behaviour when a council has no permit scheme or no data, which would round it out.

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 both parameters are documented there, so the baseline is 3. The description adds a genuine constraint absent from the schema (which lists no required fields and no oneOf): exactly one of council_name or town_slug must be supplied, which materially changes how the agent calls it.

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 (council skip permit rules) and enumerates the exact fields returned (fee, permit period, notice needed, renewal, application link, freshness). This clearly separates it from get_skip_prices and recommend_skip_size without needing to open 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?

Gives a concrete exclusion ('A skip on a private driveway needs no permit') and an input constraint ('Provide exactly one of council_name or town_slug'), which steers correct invocation. It does not explicitly name a sibling as the alternative for price or sizing questions, so it stops short of full when/when-not routing.

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 this a read-only, non-destructive, closed-world lookup, so the safety profile is covered. The description adds genuinely useful context the annotations do not: prices are indicative 2026 figures and are confirmed on the booking call with a vetted local operator, signaling the data is not authoritative.

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: scope, the required-input rule, and the accuracy caveat, in that order. Nothing is repeated and every sentence carries information the 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 usefully summarizes the return shape (low/median/high GBP per skip size) and the mutual-exclusion input rule, and annotations cover the safety profile. It does not say what happens for an uncovered area, which is a minor gap 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 coverage is 100%, which sets a baseline of 3, but the description contributes a constraint the schema does not encode: exactly one of town_slug or postcode_area must be supplied (the schema has no oneOf and zero required parameters). It also clarifies that values represent a town or a postcode area.

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 (skip hire price ranges: low/median/high in GBP per skip size) and the two input scopes (town or postcode area), which is enough to distinguish it from check_coverage, get_permit_info and recommend_skip_size. It is clear but stops short of explicitly naming how it differs from those siblings.

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?

'Provide exactly one of town_slug or postcode_area' is a real usage constraint, and the schema points to check_coverage for finding a town slug. However, there is no explicit statement of when to reach for this tool versus the sibling price/coverage/size tools, so the routing guidance is only implied.

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 destructiveHint=false, so safety is covered. The description adds meaningful behavioral context beyond that: it is rule-based and deterministic, matching the live calculator, and it enumerates what the caller receives (capacity, weight guidance, price range, calculator link).

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 tight sentences: the first states purpose and methodology, the second front-loads the return contents. No filler or repetition.

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 compensates by naming the returned fields. Nothing critical is missing for invocation, though it does not say whether the recommendation is absolute or whether alternatives are ever returned.

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 all three used inputs (job type, waste type, scale) are enumerated in the schema, so the description adds no parameter-level detail beyond naming them. It also omits mention of the optional `placement` parameter, which the schema notes never affects size. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Recommends a skip size") plus the exact inputs it derives from, and clarifies the authority behind the recommendation ("same rules as the Rent-a-Skip skip size calculator"). It does not explicitly differentiate itself from siblings like get_skip_prices, which it partially overlaps with by returning a price range.

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 implies when it is useful — sizing a job from job type, waste type and scale — but gives no explicit when-to-use/when-not guidance and never names an alternative tool. An agent can infer the use case but must reason about routing itself.

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