liftcompass

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so 'Read-only' earns no credit. What does add value is the ranking-fairness policy ('never by commission') and the affiliate-parameter policy ('only after approval'), which are real behavioral constraints not expressible in the annotation set. It stops short of covering failure modes such as invalid IDs or unsupported region combinations.

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 dense paragraph, front-loaded with the purpose and ranking rule before the telegraphic Inputs/Returns breakdown. Every clause carries information, though the Returns sentence is a long run-on that could be split for faster scanning.

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, price per serving, testing, dose, caffeine, store URL). All three parameters are described and the safety profile is covered by annotations. The missing piece is guidance on how ties or default criteria are handled.

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 carry the parameter burden — and it does, restating the 1–5 product_ids bound, the EU/US region values, and the four criteria names. It does not clarify whether omitted criteria means a default ranking or no ranking, which is the one real semantic 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?

Opens with a specific verb, resource and scope: rank up to 5 products by stated criteria, with an explicit ranking policy (never by commission). The name/title 'compare products' is vague on its own, but the description immediately disambiguates it from plan_stack and shopping_list by framing it as a criteria-ranked comparison that returns row 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?

Usage is implied by the input list and the 'never by commission' ranking rule, but there is no explicit statement of when to choose this over plan_stack or shopping_list, nor any prerequisite or exclusion. An agent can infer the context (product comparison across regions) but must reason about sibling selection on its own.

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, openWorldHint=false and destructiveHint=false, and the description is consistent with those. Beyond annotations, it adds useful behavioral context by describing the return contents: fit flags, cost, weight capacity, compatibility, third-party testing, store URLs, budget remaining, cheaper alternatives and space notes.

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 front-loaded with the core purpose and then efficiently lists inputs and outputs. Every clause adds information relevant to invoking the tool, with no wasted prose.

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 five-parameter planning tool with no output schema, the description is nearly complete: it explains inputs, output fields and the read-only nature. The main remaining gap is guidance on when to use this versus sibling 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 description coverage is 0%, so the description carries the burden and names every parameter: space_sqm, optional ceiling_height_cm, budget, goals[] with allowed values, and region with EU/US. It does not clarify finer points such as budget currency handling across regions, but overall the parameter meaning is well covered.

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 clear verb and resource: build a home gym equipment plan, with scope around space, ceiling and budget. It does not explicitly distinguish itself from siblings like plan_stack or shopping_list, but the purpose is specific enough for an agent to recognize it as the home-gym planner.

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 by the description: this is the tool for planning home gym equipment given space, budget, goals and region. However, there is no explicit when-to-use guidance, no exclusions, and no routing to siblings such as compare or shopping_list.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful behavioral context: it lists returned plan elements, safety flags, and refusal conditions. It does not describe edge cases such as conflicting budget inputs or unknown supplement names, so it is not exhaustive.

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 front-loaded with the core purpose, then compactly covers inputs, outputs, and refusals. Every sentence carries useful information, and the repeated 'Read-only' is minor and aligned with 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?

With no output schema and 0% parameter description coverage, the description does substantial work by explaining return contents and refusal boundaries. It is broadly complete for invocation, though it omits finer details such as exact age-gate behavior and how goal/diet combinations alter recommendations.

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 names all seven parameters and clarifies that diet is optional and budget_per_month or budget_tier can be used, but it does not define goal/diet semantics, budget tier behavior, or exactly how current_supplements drives duplicate-ingredient checks.

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 gives a specific verb and resource: build a supplement plan for a fitness goal. The take/skip/optional framing and supplement-specific scope make it clearly distinct from plan_home_gym and shopping_list, though it does not explicitly name sibling 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?

It provides clear usage context (fitness goal, optional diet/budget/region inputs) and explicit when-not cases by refusing medical, pregnancy, and medication scenarios. It does not route between sibling tools such as compare or shopping_list, so it falls short of full alternative 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, openWorldHint=false, and destructiveHint=false, so 'Read-only' is redundant. The description does add useful context about the output format (plain merchant URLs, estimated price, disclosure, total) and the fact that affiliate links are withheld until approval, which is a behavioral constraint 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 well structured and front-loaded: purpose first, then inputs, then outputs, then a constraint. It is efficient, with only the final 'Read-only' being redundant against the 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 one-parameter tool with no output schema, the description covers the essential inputs and return values (URLs, price, disclosure, total). It could say more about error handling or what a 'product pick' is, but the core information an agent needs to call it is present.

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 carry the full burden. It merely restates the input shape (items[] of {product_id, region}) without explaining what product_id refers to or how the EU/US region enum affects output. This adds almost no meaning 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 — 'Turn product picks into a shopping list' — and immediately describes the return payload. It is clearly distinct from the unrelated siblings (compare, plan_home_gym, plan_stack), though it never explicitly names what it is not.

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 what the tool does but offers no explicit when-to-use, when-not-to-use, or alternative guidance. There are no prerequisites or conditions that tell an agent when to choose this over another tool.

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