steel-tools

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

With no annotations, the description is responsible for behavioral disclosure. It reveals that returned values are nominal and not authoritative, which is a critical caveat for a reference tool. It also implies a read-only, lookup behavior consistent with the verbs 'describe' and 'look up'. However, it doesn't specify response format or error behaviors for unrecognized names.

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 action ('Describe... or look up'), and includes the essential caveat in the second sentence. No word is wasted.

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 one-parameter lookup tool, the description provides adequate context: what it does, what it returns (nominal values), and its limitation. Without an output schema, the description partially covers return expectations, though it could mention the exact format (e.g., text vs. structured data) 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?

The schema description already fully covers the only parameter, name_or_slug, with examples for both connection types and bolt grades. The main description reiterates this dual-purpose but adds no new semantic information beyond what the schema provides, so the baseline of 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 clearly defines the tool's function: describing steel connection types (behaviour, use, failure modes) and looking up bolt grades. The verbs 'describe' and 'look up' are specific, the resource is distinct, and it differentiates from sibling tools (gauge, plate weight, shape weight) by resource type.

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 explicitly states the intended use ('for estimating and orientation') and the exclusion ('not design guidance'), which is a strong usage boundary. It doesn't name sibling tools, but the resource differences make the appropriate context 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?

With no annotations, the description carries the full burden. It discloses that the values are 'published nominal values' and specifies contexts where they should not be used (design guidance). It also states the units returned, providing useful behavioral context beyond a simple lookup. It does not detail error behavior for out-of-range gauges, but the schema min/max provides that.

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, well-structured sentence. It front-loads the primary action and resource, states the parameter scope, and includes a necessary caveat in a compact final clause. 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?

For a simple lookup tool with two parameters and no output schema, the description provides all essential context: the range of gauges, material variants, output units, and the intended usage (estimating) with a caveat. This is sufficiently complete for an agent to select and invoke the tool correctly.

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%, so the description need not compensate. The description mentions the gauge range (3-28) and material series, but these are already captured in the parameter descriptions. It adds no new semantic information 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 explicitly states the tool looks up sheet steel gauge thickness in inches, mm, and lb/ft², for three material series. The verb 'look up' and the resource 'sheet steel gauge thickness' are specific and distinguish it from sibling tools like weight calculators.

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 when to use this tool: for estimating and orientation. It also provides a clear exclusion: 'not design guidance.' However, it does not explicitly name alternative tools for when more precise or design-grade data is needed.

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 burden of behavioral disclosure. It adds useful caveats about nominal values and design limitations, but does not disclose output format, rounding behavior, or material density assumptions beyond 'carbon steel'.

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: the first front-loads the action and key inputs, the second adds the caveat. Every word earns its place, with no unnecessary detail 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?

For a simple calculation tool with no output schema, the description covers purpose, inputs, and limitations. It does not explicitly state the output unit (pounds), but this is strongly implied by 'price_per_lb' and the domain. Slightly more detail on output would make it fully 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 100%, so the baseline is 3. The description adds little beyond the schema—it restates that thickness can be decimal or fraction and that price_per_lb is optional, but these are already in the parameter descriptions.

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 computes carbon steel plate weight from thickness, width, and length in inches, with optional cost via price_per_lb. This specific verb+resource+inputs distinguishes it from sibling tools like steel_shape_weight, which targets structural shapes.

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 context that values are nominal, for estimating and orientation, not design guidance. However, it does not explicitly mention when to use this tool versus alternatives like steel_shape_weight or steel_gauge_thickness, so it lacks explicit exclusions or alternative references.

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 burden. It discloses data source (14th-Edition-era), values are nominal, and not design guidance. This clarifies the tool's safety profile and limitations, though it doesn't describe error handling.

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, directly front-loaded with the action and outputs, no 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?

Covers purpose, inputs, outputs, and limitations. Since there is no output schema, it still specifies what fields are returned. It doesn't explicitly contrast with siblings, but the shape list provides enough differentiation.

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 has 100% coverage with descriptions for all three parameters. Description adds no param detail, but baseline is 3 for high coverage.

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 uses specific verb 'Look up' with resource 'AISC shape designation' and lists outputs (lb/ft, depth, area). It distinguishes from sibling steel_plate_weight by naming shape types (W, C, MC, L, HSS, PIPE).

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 use case (estimating and orientation) and explicitly excludes design guidance. It doesn't name alternatives, but the shape list implies the scope, providing enough context.

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