sati-grumpy

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

With no annotations, the description carries the full burden, and it does disclose the key side effect (mutating cart state) and the token return. It says nothing about auth/cart identity, whether re-adding the same SKU increments quantity, idempotency, or failure behavior on an invalid SKU — meaningful gaps for a write 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?

Two short sentences with the action and outcome front-loaded and zero filler; nothing could be cut without losing information.

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?

Return values are covered by the output schema, and the add-to-cart-then-checkout flow is conveyed. For a tool with no annotations and 0% parameter coverage, though, quantity semantics and error/auth behavior remain unstated, so it is only minimally adequate.

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 only asserts that a valid SKU is required and gives no format, validity rule, or example; the quantity parameter (default 1) is never mentioned, so its semantics — increment vs. set, valid range — are left entirely undefined.

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 ('Add a Salvage & Surplus product to your cart') plus the observable outcome ('receive a cart token'), which cleanly separates it from search_products, get_product, checkout and confirm_payment. An agent can route to it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The line 'Returns cart_token needed for checkout' implies this step precedes checkout, which gives implicit ordering guidance. However, no alternative is named, no exclusion conditions are given, and it never says the product must first be located via search_products or get_product.

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, so description carries the burden. It discloses the key chaining behavior (returns payment_token required for completion), which is valuable. However, it omits permission/auth needs, failure modes (e.g., expired cart_token), whether it mutates the cart, and rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences, front-loaded with the action and immediately followed by parameter sourcing and return value. No waste.

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 2-param, no-annotation step in a multi-step flow, the description covers the happy path and the payment_token linkage, and an output schema exists so return values needn't be spelled out. But missing failure modes, mutation semantics, and auth requirements leave notable gaps for a no-annotation tool.

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%, so description must compensate. It explains that cart_token comes from add_to_cart and that email is a billing email, adding meaning beyond the bare 'string' type. It does not describe email format/validation or error behavior for invalid tokens.

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?

Clear verb+resource: 'Initiate checkout for a cart.' It explains the outcome (returns a payment_token) which distinguishes it from siblings like confirm_payment. No explicit sibling contrast, but the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

States the prerequisite context ('Provide cart_token from add_to_cart') and that the returned payment_token is needed to complete the purchase, implying confirm_payment follows. No explicit when-not or alternatives, but usage context is 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 exist, so the description carries the full behavioral burden, and for an irreversible money-moving operation it omits critical traits: whether the payment is actually captured, idempotency/duplicate-charge protection, retry semantics, and required authorization. It only discloses the end state ('completes the purchase and returns an order confirmation'), which is thin for a payment 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?

Two sentences, zero filler, with the token requirements and the resulting outcome front-loaded. Nothing redundant.

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?

An output schema exists, so return values need no explanation, and the input roles are covered. However, with no annotations and a destructive payment action, the missing behavioral context (idempotency, auth, failure handling) leaves the definition 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?

Schema description coverage is 0% with two bare string params, so the description must compensate — and it does by defining cc_token as a credit card token and identifying payment_token's origin (checkout). It adds real meaning, though no format/validity hints are given.

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 (confirm) and resource (payment), and names both inputs and the resulting outcome (order confirmation). It implicitly separates itself from checkout by sourcing payment_token 'from checkout', but never names a sibling explicitly, so it stops short of the 5 bar.

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 'a payment_token from checkout' establishes a clear prerequisite/ordering constraint — the agent knows checkout must run first. There is no explicit when-not-to-use guidance or failure-alternative, so it is clear context without 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?

With no annotations, the description carries the full behavioral burden. 'Retrieve' implies a read-only operation, but nothing is said about permissions, behavior for an unknown/invalid SKU, or SKU case sensitivity. The output schema covers the return shape, so the remaining gap is moderate rather than severe.

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 short lines, front-loaded with the core purpose before the examples. The example SKU list occupies a full line but is justified given the 0% schema coverage on the parameter.

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 single-parameter read tool with an output schema, the description covers the essentials and supplies SKU format examples. Only edge-case behavior (invalid SKU, not-found handling) is left unstated, which is minor at this 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 description coverage is 0%, so the schema says nothing about the sku parameter beyond its type. The description compensates partially by giving concrete example values (GR-001 through GR-005), which conveys the expected format, but does not state requiredness or matching rules.

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 (Retrieve), resource (Salvage & Surplus product), and lookup key (by SKU), which is clear enough to separate it from search_products. It never names the sibling or explains the distinction explicitly, so it falls short of full sibling differentiation.

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?

There is no when-to-use statement, no when-not, and no mention of search_products as the alternative when the SKU is unknown. The 'by SKU' phrasing weakly implies a SKU is required, but the agent gets no real 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?

With no annotations, the description carries the full behavioral burden. It does disclose what kind of records come back ('matching GPU rigs, server racks...'), which is useful, but says nothing about result limits, pagination, ranking/fuzzy matching of the query, or authentication requirements.

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 lines, front-loaded with the verb+resource and followed by result types and the filter vocabulary. Every line carries information; only a small amount of polish (line fragments rather than prose) keeps it from a 5.

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?

An output schema exists, so return values need not be detailed, and the description correctly spends its budget on scope and filters. However, for a search tool with zero annotation coverage and 0% schema parameter documentation, the absence of query semantics and result/pagination behavior leaves real 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. It usefully enumerates the accepted category values (compute, servers, storage, networking, support), which the schema lacks as an enum, but leaves 'query' entirely undefined — no indication of what fields it matches (name, SKU, description) or matching semantics.

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 ('Search Salvage & Surplus product catalog') and enumerates the result types (GPU rigs, server racks, drive arrays, network gear), which makes the tool's scope immediately legible. It does not, however, differentiate itself from the sibling get_product, which an agent must choose between for discovery vs. single-item lookup.

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 explains a filter mechanic ('Filter by category: ...') but never states when to use search_products versus get_product, nor any prerequisites or conditions. An agent must infer the discovery-vs-detail split from the tool names alone.

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