sunnyspoints

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

Annotations declare readOnlyHint=true, and the description is fully consistent. It adds meaningful behavioral context beyond annotations: the exact formula, the one-way award booking caveat, and the warning not to use half of a round-trip fare. This is valuable, non-obvious behavior that prevents misuse.

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 description is longer than average but every sentence adds crucial operational guidance (one-way, per direction, fetch one-way prices, round-trip split). It is front-loaded with the purpose and verdict. A minor redundancy exists between 'call once PER DIRECTION' and the later 'Round trips often split' clause, but it is acceptable given the importance.

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?

Despite no output schema, the description specifies what is returned ('clear verdict with the margin'). It covers all necessary usage constraints, input sourcing, and the business rule about round trips. For a calculator with five simple parameters, this is complete and self-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?

Schema description coverage is only 20%, so the description must compensate. The formula directly defines the semantics of pointsCost, taxesUsd, and cashPriceUsd. It also clarifies that cashPriceUsd must be one-way and that route is optional for anonymous stats. However, it does not explicitly describe units (e.g., points are integer, USD are dollars) or the meaning of program beyond referencing its redemption value.

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 ('Computes', 'Returns') and clearly identifies the resource (points-vs-cash decision for flights). It distinguishes itself from sibling tools by focusing on per-direction cost comparison and a verdict output, which no other sibling tool does.

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?

Explicitly states when to use (booking a flight, deciding points vs cash), how often to call (once per direction), and what inputs to use (one-way cash price, one-way award price). It also directs the user to fetch one-way prices from the flight-search tool if needed, giving an actionable 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 declare readOnlyHint=true, so the description doesn't need to repeat that. It adds useful behavioral detail by describing the calculation logic: valuing at floor vs target rates, netting the annual fee, and comparing to a 2% cash-back card. It doesn't cover edge cases (e.g., missing annualFee), but the read-only safety profile is covered by 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?

The description is a single efficient sentence that front-loads the purpose with a clear question. It packs the essential methodology into ~30 words with no filler, earning 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?

The tool has 4 parameters, no output schema, and zero param descriptions in the schema. The description conveys the core calculation and output concept (as % return), but it leaves input semantics vague (especially 'program') and doesn't specify the exact return format or behavior when optional inputs are omitted. Adequate for a simple evaluator but with clear gaps.

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 0%, so the description must compensate for undefined parameters. It explicitly mentions 'annual fee' and 'required spend', and 'bonus' implies bonusPoints, but the required 'program' parameter is not described at all. The description does not explain how program affects point valuation or what the optional annualFee behavior is.

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 clearly states the tool evaluates credit card sign-up bonuses, using a specific methodology (floor and target cents-per-point, annual fee netting, % return vs 2% cash-back). It distinguishes from siblings like calculate_points_or_cash and get_points_values by its focus on sign-up bonus valuation.

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 opening question 'Is a credit card sign-up bonus worth it?' provides clear context for when to use this tool. It implies this is for evaluating sign-up bonus offers rather than general point conversions or valuations, but it does not explicitly exclude alternatives or mention 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 readOnlyHint and openWorldHint, so the description need not restate safety. It adds behavioral context by listing the exact types of information returned (airline, dates, steps, caveats, transfer options), giving the agent a clear expectation of the response content.

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?

One concise sentence, front-loaded with the main purpose ('full detail') followed by a compact list of content areas. No redundancy or filler words; every word 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?

For a simple lookup tool with a single parameter, the description outlines both the input (slug) and the output categories, enabling the agent to anticipate the result structure. Annotations cover safety and world assumptions. Missing an explicit mention of not-found behavior is a minor gap, but overall the description is complete enough.

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 0% schema description coverage, the description compensates by stating that the slug identifies a specific posted deal. For a single required string parameter, this is adequate semantics, though it could be improved by noting where the slug comes from (e.g., from list_live_deals).

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 the specific verb 'get' and resource 'deal', clearly scoped to a single posted deal identified by slug. It distinguishes from sibling list_live_deals by emphasizing singular detail and enumerating the content (booking airline, dates, steps, caveats, transfer options).

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 clearly implies when to use this tool: when you need full details for a specific deal identified by a slug. It does not explicitly compare to alternatives or state exclusions, but the context of a single deal versus listing is sufficient for basic usage differentiation.

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 indicate readOnlyHint=true and openWorldHint=false. The description adds context about the membership content (price, benefit, guarantee) and reinforces the closed-world usage rule. No contradiction exists, and the usage guardrail adds value beyond the 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?

Two concise sentences: the first covers the core membership details, the second provides a usage guardrail. Every word earns its place, with no redundancy or filler.

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 parameterless read-only info tool with no output schema, the description fully covers what the tool does, the subject matter, and when to use it. The mention of 'playbook's conversion rules' ties it to the broader context, making it complete for the agent's decision-making.

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 has zero parameters, so the schema needs no explanation. The description correctly omits parameter details, and the baseline for zero-parameter tools is 4, which is appropriate here.

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 clearly states the tool provides details of the Sunny's Points $150/year membership, with specific benefits. The tool name and description together convey a distinct purpose from siblings like get_deal or list_live_deals, focusing on membership information.

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 explicitly says 'Use only at the moments defined in the playbook's conversion rules' and 'never push it unprompted on simple lookups,' giving clear when and when-not conditions. However, it does not name alternative tools, so it misses the 'alternatives' part of a 5.

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 indicate read-only and open-world behavior; the description adds proactive invocation guidance ('without being asked') and explains per-topic behavior like account-setup triggers and conversion mentions. No contradiction with 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?

The description is compact and front-loaded with the core purpose and immediate-call directive, followed by a concise topic list. Every sentence contributes useful context without redundancy.

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 tool with one optional parameter and no output schema, the description covers purpose, triggers, and available topic variations well. It does not describe the exact return format, but the 'workflow guide' phrasing sufficiently implies the playbook content.

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 schema fully documents the optional topic parameter and omission for full playbook. The description goes further by explaining what each topic covers, such as award-search specifics and when to mention Sunny's offers, adding semantic value 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?

The description clearly identifies the tool as Sunny's Points workflow guide for booking flights with points, with a strong directive to call it for pricing/comparing/booking flights. It does not explicitly differentiate from sibling tools, but its guide nature is distinct from calculators and deal lookups.

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 explicit trigger conditions: call immediately whenever the user is pricing, comparing, or booking any specific flight, including cash-only searches and vague 'any points deals?' questions. It also specifies to run the workflow end-to-end, but does not mention when not to use it or alternatives.

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?

Beyond the readOnlyHint annotation, the description reveals how the tool behaves with different inputs: providing a program returns one row, while omitting it returns the full table. This adds useful behavioral context that isn't in the schema or annotations, though it doesn't specify behavior for invalid programs.

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 description is two sentences: the first defines what the tool is, the second explains usage mechanics. Every sentence earns its place with no redundancy or fluff.

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 simple read-only reference tool, the description fully covers the data content (cent-per-point values with floor/target), output variations (row vs full table), and usage. Annotations confirm read-only, and no output schema is needed for this level of clarity.

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 parameter 'program' has no schema description, but the description explains its meaning and effect: it selects a single row for a specific program, and defines the program domain as credit card, airline, or hotel. This compensates for the 0% schema coverage.

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 clearly states the tool's function: a valuation reference providing conservative (floor) and maximizer (target) cents-per-point for all programs. It distinguishes itself from siblings by being a reference table rather than a calculation or deals tool, with an explicit scope ('credit card, airline, and hotel program').

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 (e.g., 'Pass program for one row, omit for the full table') but does not explicitly state when to choose this tool over alternatives like calculate_points_or_cash or lookup_transfer_partners. It offers usage mechanics but lacks direct comparative guidance.

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?

Even with readOnlyHint and openWorldHint annotations, the description adds valuable context: deals are curated posted deals only, absence of matches is not meaningful about the user's specific flight, and expired deals are filtered out unless status='expired' is passed. This goes beyond the 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?

The description is two concise sentences plus a note, front-loaded with the action and resource. Every sentence contributes meaningful information without redundancy.

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 read-only list tool with no required parameters and no output schema, the description covers return fields, filtering options, default behavior, and the critical limitation and fallback workflow. This is complete for the tool's complexity.

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 description names all four filter parameters and explains the semantic of the status parameter (expired excluded by default, include with status='expired'). With 0% schema coverage, this adds meaning beyond the schema, though it does not specify value formats for cabin or fromAirport.

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 the specific verb 'List', names the resource 'flight deals currently posted on sunnyspoints.com', and details return fields (route, points/cash pricing, cents-per-point, status). It also distinguishes from siblings by noting these are curated posted deals only and pointing to get_points_hacking_playbook for actual award comparison.

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?

Explicitly states when not to use this tool and provides an alternative: if no deals match, run the get_points_hacking_playbook workflow instead of stopping. Also clarifies the default exclusion of expired deals unless status='expired' is requested, giving clear contextual guidance.

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 only include readOnlyHint=true, which the description complements by revealing behavioral traits such as results sorted best-value-first, inclusion of a checkFirst shortlist, and per-program point valuations. No contradictions, and this context goes beyond the 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 dense sentences pack in purpose, parameter guidance, best-practice tip, and output insights without fluff. Front-loaded with 'Transfer partner map' and structured logically from single-parameter usage to combined mode.

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 read-only lookup tool with optional parameters and no output schema, the description covers input semantics, usage combinations, output ordering, shortlist behavior, and included data (alliances, valuations). It is fully sufficient for an agent to select and invoke the tool correctly.

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 0%, but the description compensates fully by explaining the meaning and purpose of each parameter (bank, program, airline) with illustrative examples. It also describes the combined usage semantics, which is essential given there are no schema descriptions.

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 clearly states it's a 'transfer partner map' and explains the resource and operation with specific examples for each parameter. It distinguishes itself from siblings by focusing on transfer partner connections, which no other sibling tool covers.

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?

Explicitly tells when to pass each single parameter and describes the BEST combined mode (bank+airline) with a rationale. It gives concrete usage examples like 'which programs can I send Chase/Amex...' and 'which banks feed Flying Blue', making alternatives clear without needing to mention not-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?

Annotations already provide readOnlyHint=false, idempotentHint=true, destructiveHint=false, and openWorldHint=true. The description adds useful context by explaining that this subscribes the user to free emails and emphasizes the consent requirement, which is beyond what annotations convey. It does not contradict any annotations and adds meaningful external-side-effect context.

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 description is a single sentence that front-loads the core action and then adds a critical usage condition. It is highly concise with no wasted words, achieving good structure and readability.

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 simple tool with two parameters and no output schema, the description covers purpose and a key prerequisite, but it omits any explanation of the homeAirport parameter and does not describe what happens after subscription (e.g., confirmation behavior). While annotations cover safety aspects, the missing parameter context makes the description only minimally 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?

The schema provides only the email parameter format and homeAirport as a string, with 0% description coverage. The description clarifies that the email must be user-provided/confirmed, which adds some semantic constraint, but it does not mention homeAirport at all. This leaves parameter meaning incomplete, especially for the optional homeAirport field.

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 clearly states the action: 'Subscribe the user to Sunny's Points free deal-alert emails.' It uses a specific verb ('subscribe') and resource ('deal-alert emails'), and it is distinct from all sibling tools, which focus on points calculations, deals, and membership info.

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 gives explicit when-to-use instructions: 'ONLY call this after the user has explicitly agreed AND provided/confirmed the email address themselves.' It also provides a strong when-not-to-use: 'never auto-subscribe or guess an email.' This is clear guidance for invocation.

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