StackTheDeal Deals

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful return-policy context: results link to the offer page, the apply link lives there, and no bank or referral links are returned here. This goes beyond the annotations and clarifies what the agent should expect from the payload.

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 tightly written sentences with no filler. It front-loads the resource and returned fields, then adds link and exclusion behavior, so every sentence 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 read-only lookup with complete parameter documentation and no output schema, the description conveys enough about return shape and link behavior. It omits some minor details such as pagination semantics, but those are largely covered by the schema and annotations.

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 the kind and limit parameters are fully documented in the input schema. The description adds no further parameter syntax, defaults, or filtering semantics, making the baseline of 3 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?

The description names the specific resource (credit-card welcome offers and bank-account bonuses) and lists the fields returned, making it clearly distinct from generic deals or coupons. It does not explicitly contrast itself with sibling tools such as get_coupons or search_deals, but the domain is specific enough for an agent to identify it.

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 no guidance on when to use this tool versus related siblings like get_coupons, get_deal, or list_deals. Usage is only implied by the tool name and content type, with no alternatives or exclusion conditions 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 declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely useful behavioral detail: coupon codes are spelled out in the response and result links point only to stackthedeal.com deal pages.

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 short sentences, front-loaded with what the tool returns before the usage hint and the link caveat. No padding, though the final 'stackthedeal.com only' clause is slightly clipped in phrasing.

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, single-parameter read tool with full annotation coverage and no output schema, the description covers what is returned (deals plus coupon codes) and where links go. Nothing essential for correct invocation 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 description coverage is 100% for the single optional 'limit' parameter, so the schema fully documents it. The description adds no parameter-level information, which is the correct baseline when the schema does the work.

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 (live deals requiring a coupon/promo code) and clarifies the returned payload includes each coupon_code. It implicitly separates this from card-offer and general deal siblings, but never names an alternative to disambiguate 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?

Gives a concrete trigger phrase ('any coupon codes?' questions), which tells the agent when this tool is the right one. It stops short of stating exclusions or which sibling to use when the user asks about non-coupon deals.

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 safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower, and the description adds that the response includes liveness status — useful return-behavior context given no output schema exists. It stops short of describing behavior for an unknown/expired slug.

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 with the core action first and the clarifying parenthetical after; no filler and nothing repeated from the schema.

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 full schema coverage and no output schema, the description is nearly sufficient: it names the key, the input shape, and one salient returned attribute. Only failure behavior (nonexistent or dead-slug errors) is left unstated, a minor gap.

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 meaning beyond the schema by defining slug concretely as the last segment of a stackthedeal.com/deals/<slug>/ URL. That extra identification help is genuinely additive for recognizing a valid slug.

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?

Specific verb+resource (get one deal) scoped to a single entity, which cleanly separates it from the sibling list_deals and search_deals that operate on collections. The parenthetical explaining the slug's URL origin further pins down what a 'deal' is in this domain.

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: it fetches a single deal by slug, and the schema hints the slug comes from list_deals or search_deals. There is no explicit statement of when to prefer this over search_deals or what to do if only a name is known, and no when-not-to-use 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 already declare readOnly, idempotent, non-destructive, and open-world behavior, so the safety profile is covered. The description adds useful context beyond that: result ordering, the hours_left field, and the constraint that links point only to each deal's page on stackthedeal.com. It omits pagination/rate-limit behavior, keeping it at 4 rather than 5.

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 and ordering first, then the intended question type, then the linking caveat. No filler and nothing buried.

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-shape burden and does convey ordering and the hours_left field, but it doesn't say what other deal fields come back. That is a minor gap for a simple read tool whose annotations already cover the safety profile.

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 the schema already documents both limit and within_hours with ranges and defaults. The description only echoes the configurable 48-hour window, adding no syntax or edge-case detail beyond the schema, which matches the baseline 3.

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 (live deals) with a precise scope constraint (end time within the next 48 hours, configurable), plus ordering (soonest-ending first) and a derived field (hours_left). This naturally separates it from siblings like list_deals, get_hot_deals, and get_deal without needing to name them.

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?

It gives an explicit trigger phrase: 'Use for what deals are ending today / about to expire? questions.' That is clear usage context, but it offers no when-not guidance or named alternatives (e.g., use list_deals for all deals), so it falls short 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 establish read-only, idempotent, non-destructive, open-world behavior, so the description adds real context instead of restating them: results are 'all live and verified', ordering is deterministic, and links point only to stackthedeal.com deal pages. It does not mention pagination or what happens when fewer deals match.

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 short sentences, front-loaded with what the tool returns and the sort order, followed by the trigger condition. Every sentence earns its place with no repetition of the schema or annotations.

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 list tool with one fully documented parameter and full annotation coverage, the description covers scope, ordering, freshness, and link behavior. Without an output schema it could say a bit more about result shape, but nothing needed to invoke it correctly 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?

There is a single parameter (limit) with 100% schema description coverage including range and default, so the schema carries the full burden. The description adds nothing about the limit or result-size behavior, which matches the baseline-3 expectation when coverage is high.

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 ('deals flagged as hottest right now') and pins down the exact ordering rule (price-mistake/glitch first, then hot, newest first), which cleanly separates it from list_deals, get_deal, get_expiring_deals, and search_deals without opening their schemas.

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 an explicit trigger with a quoted user utterance: "Use for 'what are the best deals right now?' questions." It does not name alternative siblings or state when not to use it (e.g., for a specific store or category), so it stops short of full routing 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 already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint), so the bar is lower. The description adds real value by disclosing the return shape — live counts, store coverage, hot flags, and data freshness — which matters because no output schema exists. It stops short of stating refresh cadence or caching behavior, so not a 5.

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 ('StackTheDeal at a glance') and then lists the four reported facts with no filler. Every clause 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?

With no input parameters and no output schema, the description has to carry the return-value burden, and it does so clearly by naming the four data points an agent can expect. It could be slightly more complete by noting how current the 'last updated' figure is or whether the result is cached.

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 zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool is 4.

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 enumerates exactly what the tool reports — live deal count, store coverage, hot-flagged count, and last-updated timestamp — which is far more specific than the title alone. It implicitly separates itself from get_deal/list_deals/search_deals by being the aggregate site-level summary rather than a per-deal operation, though it never names those siblings 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?

The phrase 'at a glance' implies a quick-overview use case, so the intended usage is inferable, but there is no explicit statement of when to call this versus list_deals or search_deals, and no prerequisites or exclusions are given.

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 openWorld, so the safety profile is covered. The description adds genuinely non-obvious behavior: results link only to StackTheDeal pages (retailer links require following the deal page), deals are verified on the retailer's own page before posting, and results are sorted newest first.

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, front-loaded with what the tool does, followed by provenance and the link caveat. Every clause (ordering, returned fields, link destination) contributes information an agent would otherwise have to guess.

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 correctly compensates by enumerating the returned fields (price, regular price, discount percentage, store, deal link) and ordering. Read-only annotations cover safety, and all five params are documented in the schema; only filtering semantics (how store/category combine) are left implicit.

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% — limit, store, category, hot_only and min_discount_pct all carry inline descriptions with ranges and examples. The prose adds no parameter-level detail beyond the return-field list, 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?

States a specific verb and resource ('List live deals currently published on StackTheDeal'), plus scope qualifiers (live, verified on retailer's page) and ordering (newest first). It is clear what the tool returns, but it never explicitly contrasts itself with the sibling search_deals, so the agent must infer the difference from the names alone.

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: 'list live deals' with newest-first ordering suggests a browsing/feed operation, and the link caveat orients the caller. There is no explicit when-to-use-this-vs-search_deals-or-get_deal guidance and no stated prerequisites, leaving routing to the agent's inference.

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, open-world, so safety is covered. The description adds genuinely new behavior: matching is exact so aliases/fuzzy input will miss, and results are links to stackthedeal.com deal pages only. It doesn't discuss empty-result behavior, but the added context is solid.

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 short sentences, no filler, with the core scope and the exact-match constraint front-loaded before the usage example.

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 two-parameter read-only lookup with no output schema, the description covers scope, matching semantics, example inputs, intended question type, and what results contain (links to deal pages). Nothing an agent needs to call it correctly 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 description coverage is 100%, so the baseline is 3. The description goes beyond the schema by specifying exact name matching and giving accepted store-name forms, which meaningfully constrains how to fill the `store` parameter. `limit` is left to 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 a specific verb and resource plus a scope constraint ('one store, exact name match'), with concrete example values. An agent can tell this apart from list_deals/search_deals purely from the description.

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 direct usage trigger ('Use for "what deals does Walmart have?" questions'), which clearly signals the store-scoped lookup case. It does not name explicit alternatives (list_deals, search_deals) or state when not to use it, keeping it below 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 cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower. The description still adds real behavior: matching is against title/summary/store/category, and results are limited to verified live site deals, implying no expired or third-party content. It stops short of describing result shape or limit interaction.

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: purpose first, usage examples second, result scope third. Every sentence carries information and nothing is repeated from the schema or annotations.

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 low-complexity, two-parameter read tool with full schema coverage and no output schema, the description covers purpose, matching semantics, and result scope. Missing only the return shape and any routing hint away from sibling deal tools.

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 the baseline is 3. The description goes slightly beyond the schema's 'Search words' by naming exactly which deal fields the query is matched against, which directly informs query construction.

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 (search) and resource (live deals) plus the fields searched (titles, summaries, store, category), which cleanly separates it from list_deals, get_deal, and get_hot_deals. An agent can tell what it does 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?

Gives concrete user-intent examples ('find me a deal on a coffee maker', 'any LEGO deals?') that map directly onto when to call it. However, it never names an alternative (e.g., browse with list_deals, use get_hot_deals for trending), so the when-not guidance is absent.

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