BillTruth

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

With no annotations, the description carries the burden of conveying behavior. It discloses that the tool is a read-only-ish lookup returning two pieces of information (in-market status and serving TDU). It does not mention edge cases or error handling, but for a simple single-parameter lookup the behavior is reasonably transparent.

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 sentence that front-loads the essential purpose without any filler. Every word earns its place, and the structure makes the tool's behavior immediately understandable.

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 simplicity (one parameter, no output schema, no annotations), the description provides enough context for an agent to select and invoke it correctly: input is a zip, output is a yes/no plus TDU. It does not detail the return format or behavior for invalid zips, but the natural-language description is largely sufficient.

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 for the undefined 'zip' parameter. It does reference 'zip' but adds no format details (e.g., 5-digit vs ZIP+4, US-only, valid ranges). The parameter name is intuitive, but the description does not enrich it beyond the schema's string type.

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?

States a specific check: whether a zip is in the deregulated Texas market and which TDU serves it. This clearly distinguishes it from siblings like compare_plans, compare_this_house, and explain_plan, which address different domains. The resource (zip) and the two-part output are explicit.

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 intended usage is implied by the description: an agent would call this when given a zip and needing territory/market eligibility information. However, it does not explicitly state when to use it over the listed sibling tools or provide any exclusions or alternatives. No when-to-use guidance is given beyond the natural purpose.

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 behavioral disclosure burden. It adds meaningful traits: the cost is 'real twelve-month cost' rather than an estimate, and 'Returns verified_as_of with every number' signals data freshness and traceability beyond what the parameter schema provides.

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 with no filler. The primary purpose and the key output guarantee are front-loaded, and every clause adds information.

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 read-only ranking tool with fully documented parameters, the description is mostly complete: it states the selection scope, cost basis, and a return-value guarantee. It would be more complete if it described the response shape or ordering, since no output schema exists, but the current description is sufficient for correct 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 description coverage is 100%, so the schema already documents all three parameters. The description adds useful interpretive framing about monthly average usage feeding the twelve-month cost, but it does not significantly expand on the `detail` parameter or otherwise compensate beyond the baseline.

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 ('Rank') with a clear resource: 'certified Texas electricity plans for a zip.' It also specifies the ranking basis, 'real twelve-month cost at a monthly kWh average,' which makes the tool's purpose immediately distinguishable from siblings like check_territory or explain_plan.

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 contextualizes when to use the tool: when a ranked comparison of Texas electricity plans for a given zip is needed. It does not explicitly name sibling alternatives or state when not to use it, so it falls just short of a 5.

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 and does it well: it discloses that the profile is an estimate rather than Smart Meter Texas interval reads, explains the modeled fallback behavior, promises to say so, commits to never storing or repeating the street, and notes the verified_as_of field. These are meaningful behavioral details beyond the schema.

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?

Five short sentences, front-loaded with the core purpose, then usage guidance, then caveats. Every sentence adds distinct value and there is no redundant or filler 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 no output schema, the description provides strong context: what the tool ranks, when to use it, data provenance, fallback behavior, privacy, and an output field. It does not fully describe the ranking result shape, but the detail parameter and verified_as_of note cover most of what an agent needs.

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 context about the usage profile and privacy handling, but it does not add independent semantic detail about the params themselves; the schema already documents each parameter clearly.

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: 'Rank certified Texas electricity plans for a street address using a twelve-month usage profile.' It immediately distinguishes itself from sibling compare_plans by the presence of an address, so an agent can tell them apart without opening the schema.

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 instructs to 'Prefer this over compare_plans when the user has an address,' giving a clear routing rule relative to a sibling. It also explains the fallback when no usage history exists, which informs when the tool can still be used.

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 does disclose useful output traits: monthly line items, credits earned or missed, and gotchas. However, it does not state whether this is a read-only operation, what inputs are validated, or what happens when the plan cannot be found, leaving the behavioral picture incomplete.

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 and roughly 25 words. The output content and scope are front-loaded, and the second sentence directly addresses how to identify the plan. Every sentence contributes without repetition or filler.

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 three parameters, no annotations, and no output schema, this description gives a reasonable preview of the return content but leaves gaps: monthly_kwh is optional but not explained, zip format is unspecified, and no guidance is given about required territory checks or sibling-tool routing. It is adequate but not 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 only 33%, so the description should compensate. It adds high-level meaning by linking 'zip and usage' to the matching parameters and clarifies that the plan can be identified by id, slug, or name, though the latter is already in the schema. It omits format details for zip and units for monthly_kwh, so the compensation is only partial.

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 identifies the tool as producing a receipt/breakdown for one plan at a given zip and usage, which distinguishes it from sibling tools like compare_plans. However, it lacks a direct verb such as 'explains' or 'returns', relying on the noun phrase 'The receipt for one plan' to convey the action.

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 phrase 'one plan' implies this is for analyzing a single plan rather than comparing plans, so the context is somewhat clear. But there is no explicit guidance about when to use this tool versus check_territory, compare_plans, or compare_this_house, nor any when-not-to-use conditions.

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