CardPoints

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered. The description still adds value by disclosing coverage ('every UK loyalty scheme CardPoints covers') and, importantly, that each scheme's figures carry the date they were read from that scheme's own terms – a freshness/provenance caveat an agent would not get 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 front-loaded sentence that names the resource, the ordering, and the three returned fields with zero filler. Nothing could be cut without losing 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?

With no input parameters and no output schema, the description carries the return-value burden and does so by enumerating the fields returned. It could be slightly stronger by stating that results are sorted/complete and roughly how large the index is, but for a zero-arg read tool it is essentially sufficient.

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?

The tool takes no parameters, so the baseline is 4. The description correctly frames the call as a parameterless full-index retrieval and adds no misleading argument expectations.

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 and scope: a ranked index of every UK loyalty scheme CardPoints covers, with the three metrics it reports (points per £1, value per point, figures-read date). This implicitly distinguishes it from single-scheme siblings like get_loyalty_scheme, but it never names an alternative explicitly.

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 cross-scheme ranking framing suggests 'use this to compare schemes', while find_points_at_shop and get_loyalty_scheme handle narrower lookups. There is no explicit when-to-use, when-not-to-use, or named alternative.

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, closed-world), and the description adds real value on top: it discloses that results include currently running offers and a per-offer last-checked date, signalling freshness and that results are time-sensitive. It stops short of saying what happens when a shop isn't covered by any scheme, which is the main remaining 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?

A single sentence, front-loaded with the answer shape (which schemes), followed by the extra payload (offers and last-checked date). Nothing redundant or 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?

For a one-parameter, read-only lookup with no output schema, the description is nearly sufficient: it explains what comes back and that results are date-stamped. Only the empty/no-coverage outcome and result ordering are unaddressed, which is a minor gap given the closed-world annotation.

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 schema already gives the shop/brand examples, so the description adds little beyond repeating 'named shop or brand'. Baseline 3 is right when the schema does the heavy lifting.

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 and scope: which UK loyalty schemes earn points at a named shop, plus the live offers and last-checked date. It carves out a distinct role from compare_loyalty_points_value and get_loyalty_scheme implicitly (per-shop lookup vs. valuation vs. scheme detail), but never names them, so the differentiation 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?

The framing ('Which UK loyalty schemes CardPoints covers') implies you call it when you have a shop and want to know what earns there, but there are no explicit when-to-use or when-not rules and no routing to the sibling tools. Usage is inferable, not stated.

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 read-only, idempotent, closed-world behavior, so the bar is lower. The description adds genuinely useful context beyond that: the exact content returned, and that each fact carries the date it was last verified at the brand's own site, which signals freshness/data 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?

A single sentence that front-loads the scope and then lists the payload contents. It is dense but every clause carries information; only mild awkwardness in the 'One UK loyalty scheme CardPoints covers' construction.

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 telling the agent what comes back and that values are dated, which is sufficient for a simple single-parameter read tool. Only the absence of explicit routing to siblings keeps it from full marks.

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 'scheme' parameter already has examples like 'Boots Advantage Card' and 'Nectar'. The description only reinforces the one-scheme scope, adding little syntactic or interpretive meaning 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 clearly that it returns the details of a single UK loyalty scheme and enumerates what is covered (points value, earning rate, expiry, current offers). It's clear but the verb is implicit ('covers') and it never names the sibling tools, so differentiation 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?

The phrase 'One UK loyalty scheme' implies a single-scheme lookup as opposed to the comparison/point-finding siblings, but there is no explicit when-to-use or when-to-prefer-an-alternative guidance. Usage is only inferable from the scope wording.

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