STEADYWRK Field Service Dispatch

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 tool is free, includes a Store Guard $149 CTA, requires no API key, and does not provide an attested grade. These are important behavioral traits that help an agent set expectations, though it doesn't describe return format or side effects.

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, front-loaded with the core purpose, followed by important caveats. No redundant or irrelevant information, making it 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?

For a simple one-parameter tool with no output schema, the description covers key aspects: what it does, what it isn't, cost, and key requirements. It doesn't detail the return structure, but the mention of 'snapshot' and the CTA provides enough context 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?

Schema coverage is 100% for the only parameter 'url', which is described as 'Public storefront URL or domain'. The description adds minimal extra meaning, just mentioning 'storefront' and 'No API key required', which aligns with the schema. Baseline of 3 is appropriate since the schema already provides adequate 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?

The description clearly states it provides a 'storefront readiness snapshot' and enumerates specific coverage areas (UCP/ACP discovery, product schema, robots, answer-engine maps). This gives a specific verb-like action ('snapshot') and resource, but it doesn't explicitly differentiate from sibling tools like dispatch.*. However, the scope is clear enough.

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 context: it's free, requires no API key, and is not an attested grade, suggesting it's for quick preliminary checks. However, it doesn't explicitly state when to use it versus alternatives or mention any sibling tools, leaving exclusion criteria implicit.

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 provided, the description carries the full burden. It discloses the public nature and that no API key is required, and it lists the output contents. For a read-only dashboard tool, this is solid, though it omits details like error handling or 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?

The description is a single sentence that front-loads the main action and resource, then efficiently lists the metrics. No redundant filler or unnecessary details; it earns every word.

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 covers the main purpose, the type of data returned, and auth requirements. It is nearly complete, with only minor gaps like return format and edge-case behavior.

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 description adds meaning to the 'period' parameter via 'selected rolling window', but does not explain the specific enum values or default. Since the schema already defines these with self-explanatory enum names, this is adequate but not enhanced.

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 ('Return') and resource ('public evals dashboard'), lists the exact metrics included, and the mention of 'selected rolling window' ties to the parameter. It clearly distinguishes from sibling tools (dispatch.index, order, quote) as the dashboard/evals 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 implies usage: if you need the evals dashboard, use this tool. However, it does not explicitly state when not to use it or mention alternatives. Given the sibling tools, it relies on name inference rather than clear 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 burden of behavioral disclosure. It discloses that rates are STEADYWRK model rates (not BLS verbatim) and that no API key is required. This provides useful context about data provenance and authentication, though it doesn't mention potential side effects (unlikely) or output format.

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 concise sentences with no filler. It leads with the core purpose, then adds necessary context about data source and authentication. Every sentence earns 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?

For a zero-parameter catalog tool, the description covers the essential elements: what it returns, data provenance, and access requirements. It doesn't explicitly state output format or confirm read-only behavior, but the verb 'Return' strongly implies a read operation. It is complete enough for typical 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?

The input schema is empty (0 parameters), so the baseline for this dimension is 4. The description adds meaning by explaining exactly what the output contains (8 verticals, baseline rates, multiplier context), which is valuable given the schema itself offers no parameter guidance.

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 ('Return') and resource ('catalog of 8 dispatch trade verticals with baseline model rates'), clearly distinguishing it from siblings like dispatch.quote or dispatch.order. It also provides context about the rate type, making the 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 by stating it returns a catalog and mentions no API key is required, but it does not explicitly discuss when to use this tool versus alternatives like dispatch.quote or dispatch.order. No exclusions or alternative references are given, so guidance is only implicit.

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 provided, the description carries full burden and does well by disclosing key behaviors: auto-matching from active pool, masked contractor reference, and status URL. However, it omits failure modes, costs, or permission requirements, leaving some gaps.

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 sentence that front-loads the core action ('Create a dispatch work order') and packs essential behavioral details without any fluff. Every word earns 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?

For a tool with 7 parameters, a nested location object, no output schema, and no annotations, this description is too thin. It does not cover parameter meanings, edge cases, or expected response details beyond a brief mention of status URL and masked reference.

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%, and the description provides no explanation for parameters like trade, urgency, nte_cents, callback_url, or reference_id. The agent must guess semantics from types and names alone, which is inadequate for 7 params including a nested object.

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+resource ('Create a dispatch work order') and clearly distinguishes from siblings like dispatch.quote by focusing on order creation. The scope and action are 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 for creating dispatch orders with contractor auto-matching, but it does not explicitly state when to prefer this over alternatives like dispatch.quote or dispatch.evals, nor does it provide exclusions or prerequisites.

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 lists key outputs (matched contractor, cost, ETA tier, valid_for_minutes) and implies a non-mutating operation via 'Return', but does not disclose edge cases like no contractor availability, binding nature of the quote, or any authorization 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?

The description is two compact sentences that front-load the purpose and then efficiently summarize inputs and outputs. Every sentence provides value without unnecessary words 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?

The tool has 5 parameters, a nested location object, no output schema, and no annotations. The description partially compensates by listing return fields but leaves gaps: no explanation of location object requirements, optional parameter semantics, error handling, or quote validity behavior. This is incomplete for the tool's 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 only 20%, yet the description mentions only trade, location, and urgency, omitting optional parameters nte_cents and description. It adds no detail beyond the schema for the parameters it names, and does not explain the nested location structure or urgency values, so it fails to compensate for the low schema 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?

The description clearly states 'Return an instant dispatch quote for a field-service job' with a specific verb and resource, and further details inputs and outputs. This distinguishes it from sibling tools like dispatch.order and dispatch.evals.

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 obtaining a quote but does not explicitly state when to use this tool versus alternatives, nor any exclusions or prerequisites. It provides context (field-service job, instant) but lacks direct comparison to siblings.

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