ForthClear Liquidation Marketplace

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to repeat safety. It adds valuable behavioral details: non-owned orders are silently skipped, and it returns the CSV body as a string plus a suggested filename, which goes beyond annotations and gives the agent a clear understanding of output and edge cases.

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 and packs all essential information: purpose, column list, adapter note, filtering behavior, and return format. There is no fluff; every element earns its place, making it dense yet highly readable.

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 a single parameter, no output schema, and adequate annotations, the description is largely complete. It covers the return format (CSV string + filename) and the critical edge case (silently skipping non-owned orders). It doesn't address potential size limits or error handling, but these are minor for a simple read operation.

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 the single parameter order_ids. It does not explicitly explain that the parameter specifies which orders to export, nor does it clarify the relationship to 'calling seller's orders.' The description lists CSV columns and mentions skipping non-owned orders, but leaves the parameter's purpose largely implicit, forcing the agent to infer from the name and 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 the tool exports the calling seller's orders as CSV, listing exact columns (Order ID, Product, Buyer, Quantity, Total, Status, Date). It distinguishes from sibling bulk operations by its specific action and scope, and mentions it's a thin adapter over a specific API endpoint, making it 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 description clearly indicates the use case: exporting orders. It provides a caution that non-owned orders are silently skipped, which helps set expectations. However, it does not explicitly mention alternatives or when not to use it, so it lacks explicit exclusions.

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 idempotentHint annotation, the description explicitly states idempotent behavior and explains the auto-detection of carrier when only a tracking number is supplied. It also discloses the output as per-order success/failure buckets, adding behavioral insight not captured in 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 sentences long, yet packed with relevant details. It is well-structured, starting with the primary action, then noting optional parameters and endpoint specifics, without any redundant or irrelevant content.

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 lack of an output schema, the description provides a high-level summary of return buckets, which is adequate. It does not cover error handling or edge cases, but for a tool of this simplicity, the description is sufficiently complete for an agent to use it effectively.

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 no parameter descriptions, so the description compensates by explaining that carrier_name, tracking_url, and tracking_number are optional and shared across orders. It also clarifies the auto-detection behavior and the limit of 200 orders, adding essential meaning.

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: 'Mark up to 200 of the calling seller's orders as shipped' and identifies it as a thin adapter over a specific POST endpoint. This is distinct from sibling tools which handle exports, updates, or queries.

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 for bulk shipping operations and mentions idempotent re-runs and auto-detected carrier, but does not explicitly contrast with alternative tools. It lacks a clear 'when not to use' statement, but the context is sufficient for typical selection.

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 destructiveHint=true and readOnlyHint=false. The description adds meaningful context by noting it is a thin adapter over specific endpoints, applies seller-ownership filtering, and performs per-product validation. It does not reveal partial-failure behavior or response details, but it exceeds the minimum bar for a mutation tool 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 three sentences and front-loads the core action, scope, and constraints. Every sentence earns its place: what it updates, the endpoint/filter behavior, and the mode-to-value mapping. No unnecessary detail 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 3-parameter bulk mutation tool with no output schema, the description is largely complete: it covers modes, value semantics, ownership, validation, and the 200-item limit. A brief note about per-item errors or partial success would improve it, but the current level is sufficient given the tool's modest 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?

Schema coverage is high (67%), with value and product_ids descriptions already explaining allowed formats and ranges. The description adds a compact mapping of modes to value units, but this largely restates the schema's existing value description. No materially new parameter semantics are introduced.

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 opens with a specific verb and resource: 'Bulk update prices or minimum order quantities across up to 200 of the calling seller's product listings.' This clearly distinguishes it from sibling bulk tools like bulk_export_orders and bulk_mark_shipped, which handle different tasks.

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 when to use the tool—updating a seller's own listing prices or MOQs in bulk—and clarifies the seller-ownership restriction. However, it does not explicitly state when not to use it or name alternative tools for related operations, such as create_listing or get_pricing_recommendation.

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 this is a write operation (readOnlyHint=false), so the description adds no behavioral depth. It does not mention duplicate SKU behavior, required permissions, success/error responses, or side effects beyond the basic create 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 filler or redundant wording. It is front-loaded and easy to parse, though it sacrifices informative value for brevity.

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, 8 parameters, and no explanation of behavior or return values, the one-sentence description is insufficient for an agent to confidently invoke the tool. Critical context like required fields, pricing units, and expected outcomes is absent.

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 38%, but the description provides no information about the 8 parameters or their relationships. It does not compensate for the undocumented fields like sku, name, category, quantity, or description.

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 ('Create') and resource ('product listing'), and adds the seller-tool context. This clearly distinguishes it from sibling tools like bulk_update_listings, which update existing listings rather than create new ones.

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 '(seller tool)' implies this is used when a seller wants to create a new listing, but the description provides no explicit when-to-use guidance, exclusions, or comparison with alternatives. Usage is implied rather than 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 indicate read-only and non-destructive operations, and the description aligns with that. However, it doesn't disclose that the recommendation is AI-powered (hidden in title, but in simple form) or any limitations such as the model's reliance on category/condition. It adds minimal extra value beyond 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 extremely concise, just one sentence, and front-loads the key idea. It is not verbose, but could be slightly more informative without losing 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?

With no output schema and minimal description, the tool is inadequately documented for a complex AI-driven recommendation tool. The purpose is clear, but what the response looks like (e.g., recommended price, confidence) is missing. Sibling distinction could help.

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 describes 'condition' and 'original_retail' in detail (liquidation grade, currency units), with 50% coverage. The description adds no additional parameter semantics; it merely repeats the tool's purpose. Given the moderate coverage, this is acceptable but not compensating.

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 that the tool provides AI-powered pricing recommendations for inventory and identifies it as a seller tool. However, it doesn't explicitly contrast with siblings like 'create_listing' or 'bulk_update_listings' that might also use pricing data.

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 provided on when to use this tool versus alternatives, such as when setting initial prices vs. updating existing ones. The description doesn't mention any prerequisites or exclusions.

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?

The description adds no behavioral details beyond the annotations. It does not clarify side effects, caching, rate limits, or data freshness. Given the annotations already indicate read-only and non-destructive behavior, the description contributes little extra transparency.

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, succinct sentence with no superfluous words. It is directly to the point and well-structured.

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 lacks essential context: it does not specify what fields are returned, any error conditions, or how this tool fits into broader workflows. With no output schema, the agent is left with insufficient information to reliably use the tool. The presence of many siblings further highlights the missing guidance.

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 only parameter, product_id, is already fully described in the schema with format guidance ('product_123'). The tool description adds no further semantic meaning, so it does not enhance understanding beyond the schema. This meets baseline coverage, but no extra value is provided.

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 action ('Get') and target ('detailed information about a specific product'), making its purpose understandable. It distinguishes itself from sibling tools like get_pricing_recommendation by focusing on generic product details, though it could be more specific about what 'detailed information' entails.

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 no guidance on when to use this tool compared to siblings. It does not mention scenarios where this tool is preferred over others (e.g., when full product info is needed vs. pricing only), leaving the agent to infer usage from the name alone.

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 and destructiveHint=false, so the safety profile is covered. The description adds the scope of 'pending' and 'seller's products,' which is useful context beyond annotations. It does not describe return format or pagination, but that is not critical given the simple nature.

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, precise sentence with no redundant information. It is appropriately sized for the tool's simplicity and front-loads the key action and scope.

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 is minimally sufficient but leaves gaps. It does not explain what the response contains or how the status parameter affects results. It could also clarify that 'all' returns all requests, not just pending, but the enum makes it somewhat obvious.

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% – the description does not mention the 'status' parameter at all. Although the parameter has an enum and default that are self-explanatory, the description fails to compensate for the low coverage, leaving the agent to infer the parameter's purpose from its name and enum values.

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 (get), the resource (quote requests), and the scope (pending for seller's products). It distinguishes from sibling tools like request_quote and respond_to_quote by indicating it is a seller-facing retrieval tool.

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 indicates it is a seller tool and focuses on pending requests, which implies it is for retrieving incoming requests rather than responding. However, it does not explicitly mention when to use it over alternatives like search_inventory or seller_inbox_summarise.

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 indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=false, which already signal that this is a mutating, non-idempotent operation. The description adds context about the conditions (instant checkout, bulk threshold) but does not disclose additional behavioral traits such as whether the purchase is final, if it charges immediately, or if there are any side effects beyond the purchase. With annotations covering the basic safety profile, a score of 3 is appropriate.

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 purpose and conditions, and includes a clear alternative. Every word earns its place, with no fluff or repetition.

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 tool's moderate complexity (6 params, 3 required), the description covers the core purpose and usage conditions. There is no output schema, but the description doesn't need to explain return values. It could mention what happens after a successful purchase (e.g., order confirmation) but the current description is sufficient for an agent to decide when to use it. The sibling context and annotations provide additional 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?

Schema description coverage is 100%, so all six parameters are described in the schema. The description does not add any parameter-specific semantics beyond what the schema provides. The description mentions 'orders under bulk threshold' but does not explain how quantity relates to that threshold. Baseline 3 is appropriate since 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?

The description clearly states the tool's purpose: 'One-step purchase for products with instant checkout enabled (seller opt-in) and orders under bulk threshold.' It specifies the verb (purchase), the resource (products), and the conditions (instant checkout, bulk threshold), which distinguishes it from the sibling tool request_quote.

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 states when to use this tool: for products with instant checkout and orders under bulk threshold. It also provides an alternative: 'For products without instant checkout or larger orders, use request_quote instead.' This is clear guidance on when to use and when not to use, naming the alternative 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 provide readOnlyHint=false, indicating this tool mutates state (creates a quote request), which is not contradicted by the description. The description adds that it's a buyer tool, but does not disclose details like whether it sends an email or creates a pending request, which would be helpful. Given annotations, a 3 is appropriate.

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 that front-loads the core purpose and audience. It is efficient and free of redundancy, making every word earn 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 is moderately complex with 7 parameters, but the schema thoroughly covers them. The description is minimal, and with no output schema, the agent might not know what to expect in the response. However, given the simplicity and schema richness, a 3 is fair.

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 all seven parameters, including the required product_id, quantity, and buyer_email. The description does not add further semantic detail beyond what the schema provides, so a baseline of 3 is suitable.

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 (request a bulk quote) and the resource (product), and identifies it as a buyer tool. It distinguishes this from sibling tools like 'get_quote_requests' (seller side) and 'respond_to_quote' (seller action), making its purpose 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 description implies usage: it's for buyers to request a bulk quote, as opposed to quick_buy (immediate purchase) or get_pricing_recommendation (non-binding price suggestion). However, it does not explicitly state when to use it versus alternatives or when not to use it, leaving some ambiguity.

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 this is a mutating operation (readOnlyHint=false) and not destructive, but the description adds no behavioral detail about what happens on accept/counter/decline, whether the message is required, or side effects. It only reiterates the action's basic direction (seller responding to buyer), so it provides minimal transparency 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 a single, front-loaded sentence with no filler or redundant phrasing. It earns its place, though its brevity comes at the cost of needed detail in other dimensions.

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 four parameters, multiple enum actions, and no output schema, this tool needs more context than a one-sentence summary. The description doesn't mention what the response does, what required parameters mean, or what the outcome looks like, leaving an agent to guess about the tool's behavior. It is definitely under-specified for its 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 input schema has 25% description coverage (only counter_price is documented), and the description contributes nothing about parameter meaning, types, or relationships. For example, it doesn't explain that action must be one of accept/counter/decline, or that message is optional for accept/decline, or how counter_price is interpreted. With low schema coverage, the description's silence is a significant gap.

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 action ('Respond') and the resource ('a buyer's quote request'), and adds the seller-tool context. However, it doesn't explicitly differentiate from sibling tools like get_quote_requests or request_quote beyond the verb, so it is clear but not strongly distinguishing.

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 offers no guidance on when to use this tool versus alternatives such as get_quote_requests or request_quote, and provides no conditions for accepting, countering, or declining. It only states a generic context ('seller tool'), which does not help an agent choose among the quote-related tools.

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 and destructiveHint false, covering the safety profile. The description adds the behavioral scope 'available liquidation inventory,' implying only available items are returned. However, it does not disclose other behaviors like pagination, ordering, or response format. Consistent 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 a single, front-loaded sentence with no redundant words. It communicates the core action and scope immediately.

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 leaves the response format unspecified. It covers the basic purpose but lacks details on filter semantics, result set structure, or pagination. Given the tool's simplicity, it is minimally complete but could be better.

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 67%, but the description adds no parameter-specific meaning. The generic phrase 'with filters' does not clarify parameters like min_discount or limit, which lack full descriptions in the schema. It fails to compensate for the uncovered parameters.

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 ('search') and a specific resource ('available liquidation inventory'), clearly distinguishing this from sibling tools like bulk_export_orders, create_listing, or quick_buy. The phrase 'with filters' implies a flexible search capability. It is not a tautology.

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 no explicit guidance on when to use this tool versus alternatives. It does not mention any sibling tools, exclusions, or preferred scenarios. The usage is only implied by the tool name and description, not actionable 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 readOnlyHint=true and destructiveHint=false, so the read-only nature is covered. The description adds behavioral context by specifying the three buckets of information and reaffirms 'Read-only digest', which is consistent. It doesn't introduce new security or mutation concerns, and the added detail about content 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 sentences, front-loaded with the digest contents and followed by a concrete use case. Every word earns its place—no redundancy, filler, or restating of the title. It is highly compact and informative.

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 tool with no output schema, the description adequately explains what the digest includes and when to use it. It does not detail the output format (e.g., counts vs. items), but given the tool's summarize nature and the presence of sibling tools for granular details, this is acceptable. The safety profile is covered by annotations, so the description is complete enough for selection and 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?

The input schema covers 100% of the two parameters (limit and window_hours) with descriptions, including defaults and bounds. The tool description does not add extra parameter semantics beyond restating the input's purpose. Since schema coverage is high, the baseline of 3 applies; no additional value is provided.

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 ('summarise') and resource ('seller's inbox') and enumerates concrete content categories: pending quote requests, at-risk orders, and reported issues. This clearly distinguishes it from sibling tools like get_quote_requests or bulk_mark_shipped, which focus on single actions or data types.

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 states the intended context: 'Useful for a daily standup or cron-driven agent that decides which bulk action to run next.' This clarifies when to use it, aligning with the decision-making workflow. It does not explicitly mention when not to use it or name alternatives, but the use case is clear and enough for an agent to select it appropriately.

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