framebench

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

No annotations provided, but description details the return values (fps range, limiting component, etc.), giving a clear picture of the tool's behavior. It does not disclose potential error cases or mutation vs read, but the purpose is well-conveyed.

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 sentence, front-loaded with the core question, no extraneous information. Highly concise 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?

Despite no output schema, the description lists all expected return fields. With 6 parameters and no annotations, it provides a clear picture of inputs and outputs, though it could mention required parameter 'game' more explicitly.

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 parameters are documented. Description adds no additional parameter-level information beyond the schema, earning the baseline score of 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?

Description clearly states the tool's purpose: checking if a rig can run a game and listing the returned outputs (fps range, limiting component, etc.). It distinguishes from siblings 'compare' and 'recommend_upgrade' by focusing on a single configuration.

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?

Description implies usage (checking a game-rig combo) but does not explicitly state when to use this tool vs alternatives like compare or recommend_upgrade. No exclusions or prerequisites mentioned.

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 full burden. It mentions the output includes spec facts and a canonical URL, but does not disclose whether the operation is read-only, any side effects, authentication needs, or behavior on invalid input. This is adequate but not thorough.

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 of 20 words, front-loading the action and parameters. Every word adds value, with no redundancy.

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 low complexity (2 string params, no output schema), the description covers the core purpose and output. It lacks details on error handling or validation, but overall sufficiently defines the tool's function.

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% with simple descriptions ('name or slug'). The tool description adds semantic context by specifying that the parameters represent GPUs, CPUs, or Apple chips and that they are compared on the framebench index, going 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 clearly states the tool compares two GPUs, two CPUs, or a GPU vs an Apple chip on the framebench performance index, with spec facts and the canonical URL. It uses a specific verb 'compare' and resource type, and distinguishes well from sibling tools 'check_game' and 'recommend_upgrade'.

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 context on when to use the tool (to compare hardware sets) and what the output includes, but does not explicitly state when not to use it or suggest alternatives. The specificity of input types offers implicit 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 provided, so description must carry full burden. It only states what the tool returns but fails to disclose behavior like handling of invalid inputs, no-upgrade cases, or ranking criteria.

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?

Single sentence, front-loaded with key information, no wasted words.

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?

No output schema, no annotations. Description lacks details on output format, ranking criteria, and default behaviors (e.g., resolution default, target_fps default 60). Incomplete for reliable agent use.

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 high (80%), so baseline is 3. The description adds minimal parameter context, only mentioning 'game + resolution + fps' but not explaining 'current_gpu' or 'max_results'.

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 returns the smallest GPU upgrades that clear a target, with specific verb 'return' and resource 'GPU upgrades'. It distinguishes from siblings 'check_game' and 'compare' by focusing on upgrade recommendations.

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 use when needing upgrade recommendations but does not explicitly state when not to use or provide alternatives. No mention of siblings or exclusions.

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