QuoteOS

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

With no annotations provided, the description carries the behavioral disclosure burden and largely succeeds. It discloses partial-data acceptance, speed ('Quick'), early gating ('after 2-3 fields'), and the blocking of known-decline scenarios before adapter dispatch. It does not state whether the operation has side effects or how errors surface, but the presence of an output schema reduces the need to document return shape in prose.

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 concise and well-structured: the first sentence states the core purpose, and the second paragraph gives a direct usage mandate. Each sentence earns its place, with no filler, repetition, or restating of schema content.

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 100% schema coverage, the presence of an output schema, and the simple two-parameter interface, the description is nearly complete. It tells an agent what the tool is for, when to call it, and what behavior to expect. It only slightly underspecifies what happens when no hard stop is found, but the output schema likely covers the result shape.

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 even though the description adds little parameter-specific detail. The phrase 'partial data' loosely reinforces the meaning of fields_json, but the schema already documents both parameters clearly, including examples for auto and homeowners values.

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 opens with a specific verb and resource: 'Quick pre-flight eligibility check with partial data.' It further explains that the tool 'surfaces hard stops' and 'blocks known-decline scenarios before any adapter dispatch,' which clearly distinguishes it from the sibling quote-generation tools and establishes its role as an eligibility gate rather than a quote producer.

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 gives an explicit usage directive: 'Use this FIRST in any intake flow,' and explains the rationale by noting it surfaces hard stops after only 2-3 fields and blocks known declines before any adapter dispatch. It does not explicitly name the sibling tools or state when not to use it, but the 'before any adapter dispatch' phrasing implies the intended sequencing.

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 must disclose behavior itself. It only says 'run the full pipeline' and does not state whether the call is read-only, mutates state, calls external systems, requires eligibility first, or returns structured quotes. There are no behavioral traits disclosed beyond a vague process noun.

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 brief and front-loaded, which is good, but the brevity is under-specification rather than efficient compression. The single sentence states the action but leaves important operational detail unstated.

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 what is described as a full quoting pipeline, this is incomplete: no prerequisites, expected behavior, side effects, or relation to the sibling tools. An output schema may describe return values, but it cannot compensate for the missing operational context an agent needs to call this complex 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?

The input schema already covers the single parameter with a detailed description and required keys, so schema coverage is 100%. The tool description adds no parameter-specific meaning, 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 names a specific action ('Run') and resource ('full auto insurance quoting pipeline'), and the word 'auto' separates it from the home/eligibility siblings. However, it is a little vague because it describes the pipeline rather than the actual result (insurance quotes), so it is not a 5.

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 guidance about when to call this tool versus checkEligibility or getHomeQuotes. The word 'auto' only weakly implies the distinction, and no exclusions, prerequisites, or alternative conditions are stated.

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 of disclosing side effects, required permissions, pipeline side effects, or whether the operation is read-only. 'Run the full ... pipeline' hints at a multi-step process but does not reveal whether it mutates data, calls external services, needs prior eligibility checks, or what happens on failure. The behavioral surface is essentially undisclosed.

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 with no filler or repetition, and the core action is front-loaded. It is appropriately brief for a tool with one well-documented parameter. It lacks nuance, but from a purely structural and conciseness standpoint it is efficient.

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?

Although the output schema exists and the sole parameter is well documented, the description is too thin for a pipeline-style tool. It does not explain what 'full pipeline' means, what inputs the caller must have ready, whether eligibility is a prerequisite, or any side effects. Given no annotations, the description alone leaves significant gaps for an agent deciding whether and how to invoke this 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 100% and the schema itself gives a detailed description of home_input_json, including required keys and a pointer to engine/validator.py. The tool description adds no parameter-level meaning beyond the schema, so the baseline of 3 is appropriate since the schema already does the heavy lifting.

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 action ('Run') and a specific resource ('the full homeowners insurance quoting pipeline'), which distinguishes it from the auto quoting sibling and implies a broader scope than checkEligibility. However, it does not explicitly name alternatives or explain what 'full pipeline' entails, so it stops 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 guidance on when to use this tool versus the siblings checkEligibility or getAutoQuotes. The description implies it is for full homeowners quotes, but it never states exclusions, prerequisites, or alternative conditions. An agent must infer the intended use case from the tool name alone.

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