Cancel My Sub

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds genuinely useful behavior beyond them: 'Nothing is stored' (no persistence), the exact returned payload contents, and the alert schedule (9am day before and 9am on the day). It stops short of describing how the .ics is delivered or any size/attachment limits.

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 primary purpose and the return artifact in the first sentence, then the payload detail, then the no-persistence note. The trailing sentence about /v1/cancel is the weakest link – it describes an API endpoint contract rather than the tool itself, mildly diluting focus.

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 carries the return-value burden and does so well by naming the .ics contents and event timing. The remaining gap is practical: an agent is not told how to hand the file back to the user (attachment vs link) or what to do if the deadline has passed.

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 all three parameters (country, service, renews_on) are already documented in the schema, including the GB/UK country fallback behavior. The description only alludes to renews_on ('whenever renews_on is given') and adds no syntax or edge-case detail beyond the schema, 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 verb+resource with the exact artifact produced: a calendar file (.ics) with an all-day event on the cancel-by day containing steps and the official link. This clearly separates it from get_cancel_steps (returns steps) and list_services (enumerates subscriptions), so an agent can route without opening the 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?

The description implies usage ('calendar reminder for the last safe day to cancel') and notes the condition under which /v1/cancel surfaces this link, but it never states when to choose this tool over get_cancel_steps or what to do when the cancel-by day has already passed. Usage is inferable, not 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 cover safety (readOnly, idempotent, non-destructive), but the description adds real behavior: UK answers carry region 'UK' and uk_rules, and a US-only service queried from the UK is tagged 'US only'. That conditional output behavior is not derivable from the annotations or 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?

Front-loaded with the core purpose and return contents, then usage examples, then the regional caveat. The example list is slightly long but each example disambiguates a different subscription type (gym, streaming, membership), so it earns its space.

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 convey return shape, and it does (page, steps, catches, cheaper option, region/uk_rules). For a 3-param read-only tool this is essentially complete; only explicit sibling routing 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 coverage is 100%, so baseline is 3, but the description adds cross-parameter meaning the schema does not spell out — how country interacts with service (US-only + UK caller → region 'US only') and what renews_on produces in the answer. This genuinely supplements the structured fields.

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+resource ('How to cancel one subscription') and enumerates what it returns (official page, steps, catches, cheaper option), which is well beyond a tautology. It does not explicitly distinguish itself from siblings like get_cancel_reminder, but the purpose is unambiguous.

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 example utterances ('how do I cancel Netflix?', 'cancel my PureGym') give an agent clear triggering contexts, which is strong implied when-to-use guidance. It stops short of naming alternatives or stating when not to use it versus get_cancel_reminder or list_services.

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 the safe read-only, idempotent profile, so the bar is low. The description nonetheless discloses useful behavior the annotations cannot: it may return a single likely service, an ambiguous candidate set with verification pointers for Apple/Amazon/Google/Microsoft, or a 'match: purchase' classification for one-off orders.

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 examples are front-loaded and the tool's actual behavior follows immediately, with the chaining hint last. The return-value sentence is somewhat run-on with its stacked 'or... or...' clauses, 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 carries the burden of describing return values and does so adequately, including the ambiguity case and the purchase classification. The only gap is the slightly mismatched sibling name 'getCancelSteps' versus the actual 'get_cancel_steps', which could briefly confuse a chaining agent.

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 single 'text' parameter, including its 120-character limit. The description adds no formatting rules or normalization guidance beyond what the schema states, 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 opening sentence merely echoes the title, but the body pins down the resource precisely: it maps a raw statement string to the service that generated it. The examples (APPLE.COM/BILL, AMZN Digital, DD *DOORDASH DASHPASS) leave no ambiguity about what input it consumes.

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 quoted example utterances give an agent concrete trigger conditions, and the closing 'Then call getCancelSteps' establishes the downstream workflow. It never states when NOT to use it or contrasts it with siblings like list_services, so it stops short of an explicit routing rule.

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 readOnly, idempotent, non-destructive, and non-open-world behavior, so the safety profile is covered. The description adds non-obvious payload information — that the response also carries the FTC click-to-cancel rule status and UK rules (uk_rules) — which the agent could not infer from the schema or 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?

Three front-loaded sentences with no fluff, and the extra-return disclosure is placed at the end where it belongs. The opening sentence duplicates the title verbatim, which is a small redundancy rather than a structural problem.

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 names what comes back (covered services plus FTC and UK rule status). Combined with the schema's full parameter documentation, an agent has enough to call it correctly; only the exact shape of the returned service list is unstated.

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%; the country and category parameters are fully documented in the schema, including the GB/UK exclusion behavior and the category list. The description adds nothing about filtering semantics beyond that, 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 resource — the catalog of subscriptions the service can cancel — and the query intent it answers, which clearly separates it from siblings like get_cancel_steps and identify_charge. It never names those siblings explicitly, so differentiation is inferable rather than stated.

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?

Two concrete example phrasings ('which subscriptions can you help me cancel?', 'what gyms do you know?') give clear usage context. It stops short of any when-not-to-use guidance or explicit routing to the sibling tools for cancel steps, reminders, or charge identification.

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