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

With no annotations, the description carries full burden for behavioral disclosure. It only says 'registers a new reservation watch' and does not explain that this creates an ongoing monitor, that it may search Naver, that it can auto-book or ask for approval based on mode, or what side effects occur. The parameter descriptions in the schema cover some details, but the core behavior is undisclosed.

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 one short sentence, which is efficient but under-specified for a tool with 10 parameters and 5 required fields. It front-loads nothing useful beyond the name itself. The extreme brevity comes at the expense of conveying any operational detail, so it is not appropriate conciseness.

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 complex tool with 10 parameters, no annotations, and only a one-line description, the definition is severely incomplete. It fails to explain prerequisites (e.g., Naver login), the lifecycle of a watch, what successful registration returns (even though an output schema exists), and how mode affects behavior. An agent cannot confidently invoke this tool correctly from the description alone.

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 tool description adds no parameter-level meaning beyond the schema, but the schema itself richly defines parameters (mode, time_priority, store_url, etc.). Thus the description neither helps nor harms parameter understanding.

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 ('등록합니다' / registers) and resource ('새 예약 감시' / new reservation watch), making the core purpose clear. It does not explicitly differentiate from sibling tools like reserve_now or check_availability, but the noun-phrase 'reservation watch' is distinct enough from immediate reservation actions.

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?

No guidance is given about when to use this tool versus alternatives. The description does not mention that this tool is for monitoring future availability, nor does it distinguish itself from reserve_now (immediate booking) or check_availability (one-time check). The schema hints at modes but the description provides no usage context.

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?

With no annotations provided, the description carries full responsibility for disclosing side effects. It only says 'approve or reject' without mentioning consequences like triggering a reservation or ignoring the proposal, though the schema hints at behavior for the approve parameter. This is insufficient for a mutating action.

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 concise sentence with no redundancy. It states the purpose efficiently without any 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 two-parameter tool with a full schema and an output schema, the description covers the core action and context (ASK mode). It doesn't address usage vs siblings, but that's a usage guideline gap rather than completeness. Overall, it's adequate for the tool's simplicity.

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% for both parameters, so the baseline is 3. The description adds no extra meaning beyond the schema, relying entirely on parameter descriptions already present.

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 action ('approve or reject') on a specific resource ('reservation proposal found in ASK mode'). It is clear and distinguishes from siblings that handle watch management or direct reservation, though it doesn't explicitly name alternatives.

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 context (ASK mode proposals) but doesn't explicitly state when to use this tool versus siblings like reserve_now or reservation_status. No exclusion criteria or conditional guidance is provided.

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?

With no annotations, the description carries the full burden. It discloses that the lookup happens through the watcher service with a real browser, which is meaningful behavioral context. Yet it does not mention potential delays, dependency on the watcher service, failure modes, or the effect of timeout_sec beyond its name. Some transparency is provided, but gaps remain.

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, front-loaded with the core purpose and followed by concise parameter-mode guidance. The parenthetical is used efficiently. It could be bulleted for even faster parsing, but the current structure is clean and free of 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?

Given the output schema exists and the tool has 6 optional parameters with no annotations or schema descriptions, the description covers the main modes and real-browser behavior reasonably well. It leaves moderate ambiguities (e.g., required parameters when watch_id is absent, relationship between store_name and store_url, behavior on invalid inputs), but these are minor enough that an agent can make a correct first call.

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 explain parameters. It does so effectively by mapping watch_id to a reuse mode and store_name/store_url + target_date + party_size to a direct-query mode, adding clear semantic grouping. It does not explain timeout_sec or clarify whether store_name and store_url are alternatives or both required, but overall it adds substantial meaning beyond the raw 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 states the tool checks available reservation times in real time ('지금 이 순간 예약 가능한 시간을 확인합니다') and distinguishes two invocation modes (watch_id vs direct parameters). It does not explicitly contrast with siblings, but the verb-resource pairing is specific enough to separate it from reservation_status or reserve_now.

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 provides clear instructions for using the tool: provide watch_id to reuse watch conditions, or directly specify store_name/store_url, target_date, and party_size. However, there is no guidance on when to choose this tool over its siblings (e.g., reservation_status) and no exclusions or prerequisites are mentioned. Usage context is implied rather than 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?

No annotations are provided, so the description carries the burden. It signals a non-destructive read by saying 'returns', and adds the behavioral nuance 'currently registered'. However, it does not mention ordering, pagination, or whether this is purely read-only, though these are minor for a simple list operation.

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, front-loaded Korean sentence with no unnecessary words. It is appropriately sized for a simple list operation, though it is minimal and could include usage context without becoming verbose.

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?

Given the low complexity, one optional parameter, complete schema documentation, and an output schema, the description is nearly sufficient. Missing usage guidance and explicit read-only wording are gaps, but they do not block correct invocation.

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 parameter semantics are already fully documented: include_inactive controls whether RESERVED/EXPIRED/CANCELLED statuses are included. The description adds no extra parameter context, but none is needed 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 states a specific verb and resource: it returns the currently registered reservation watch list. This distinguishes it from add/remove/status siblings, though it does not explicitly name an alternative.

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 implied: the tool returns the list of existing reservation watches FAQs. There is no explicit statement about when to choose this over siblings, but the naming and sibling set make the intended use reasonably clear.

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?

No annotations are provided, so the description carries the full burden. It states that the tool deletes a reservation watch, but does not disclose irreversibility, side effects, required permissions, or what happens if the watch_id does not exist. For a destructive operation this is thin.

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, front-loaded Korean sentence with no filler or redundancy. It states the action and object efficiently.

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 is simple with one parameter and an output schema, but the description lacks usage guidance and behavioral caveats. It is minimally sufficient for basic invocation, but not rich enough to fully guide an agent around failure modes or consequences.

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 watch_id is adequately described in the schema. The tool description adds no parameter-level meaning, but with full schema coverage, 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?

The description uses a specific verb, '삭제합니다' (deletes), with a clear resource, '등록된 예약 감시' (registered reservation watch). This makes the tool's purpose immediately distinct from siblings like list_reservation_watches, add_reservation_watch, and check_availability.

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 alternatives, nor does it state any conditions or exclusions. The only hint about finding watch_id appears in the schema parameter description, not in the tool-level usage 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says the tool checks status categories; it does not mention side effects, permissions, freshness, or what happens when no watch_id is given beyond what the schema already says.

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 short Korean sentence with no filler; the core purpose is front-loaded. This is appropriately sized for a simple status tool whose only parameter is already fully documented in 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?

The optional parameter is fully documented and an output schema exists, so return values do not need to be described. However, with no annotations and no sibling differentiation, the description leaves the agent to infer when to use this tool and what behavioral guarantees exist.

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 watch_id field description fully explains the conditional behavior (detailed status + event log vs. summary + successful reservations). The tool description itself adds no parameter semantics, 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 operation ('확인합니다' – checks) on a specific resource (reservation success/failure/pending status). It is not a tautology and is distinguishable from action-oriented siblings like approve_reservation and reserve_now, though it does not explicitly differentiate from list_reservation_watches.

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?

No guidance is given on when to use this tool versus list_reservation_watches or other siblings. The input schema's conditional behavior (watch_id present vs omitted) provides parameter-level context, not tool-selection 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?

With no annotations, the description carries the full behavioral burden, and it does so thoroughly. It discloses automatic stops on payment, prepayment, deposit, cancellation fees, captcha, and additional authentication; it also explains the final pre-click revalidation and the dry_run side-effect guarantees of no DB record and no completion notification.

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 dense but every sentence serves a purpose: the main action, the safety stop conditions, watch_id usage, and the dry_run mode. The critical behavioral details are front-loaded, and the length is justified by the high-risk nature of the tool.

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 description is quite complete for a complex, mutation-capable tool: it covers real booking, safety gates, dry_run semantics, and watch_id behavior. Minor gaps remain around timeout_sec and the exact interplay of store_url, store_name, party_size, and target_date, but the output schema and descriptive parameter names mitigate this.

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. It explains dry_run, watch_id, and the role of time, but store_url, store_name, party_size, target_date, and timeout_sec remain largely undefined. This is a partial compensation, not a complete one.

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 immediately states that the tool attempts an actual reservation immediately under specified conditions, with a clear verb and resource. It also distinguishes the real-booking mode from dry_run mode, making its purpose unambiguous relative to the watch-management 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?

The description provides clear usage context: use watch_id to reuse a registered watch's details Bennett, and use dry_run=True specifically to verify that the real reservation flow still works safely after a site change. It does not explicitly contrast with check_availability or approve_reservation, but the intended cases are clear enough.

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