energyai

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

No annotations provided; description only states 'Free; usage tracked' and 'Submit one question answer,' lacking details on side effects, idempotency, or error conditions.

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?

Extremely brief but at the expense of clarity. The single-line description with '[free]' is too terse for a tool with four parameters and no structured metadata.

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 complexity (multiple required parameters, no output schema, no annotations), the description fails to provide essential context about answering assessment questions, expected input formats, or return 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?

With 0% schema description coverage, the description adds no meaning to the four parameters (assessmentId, questionKey, answerValue, answerLabel). The agent gets no help understanding what each parameter represents.

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 'Submit one question answer' clearly indicates the action ('submit') and the resource ('one question answer'), differentiating it from sibling tools like complete_energy_assessment.

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?

No guidance on when to use this tool versus alternatives (e.g., complete_energy_assessment). Only mentions 'Free; usage tracked,' which hints at cost but not usage context.

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. It discloses that the tool is free, requires no API key, returns US data via DSIRE, and gives qualitative official guidance for other countries. It does not detail error handling, response format, or data freshness, but covers key behavioral traits beyond basic purpose.

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 only about 80 words, with two clear sentences. It is front-loaded with the core purpose and efficiently covers scope, usage, and features without any filler. Every sentence adds value.

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 2 simple parameters, no output schema, and no annotations, the description adequately explains inputs and expected output types. It could be more complete by mentioning error handling or result format, but for its simplicity, it provides sufficient context for an agent to use 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%, with both parameters documented. The description adds clarity by specifying US 5-digit ZIP vs other postal codes, and that country is an ISO code to omit for US. This enhances the schema definitions, especially the behavioral difference between US and non-US inputs.

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 provides clean-energy incentive guidance for any address worldwide, with specific differentiation between US (federal status + state/utility programs via DSIRE) and other countries (qualitative national guidance). Verb 'check' and resource 'incentives' are explicit, and it distinguishes itself from sibling 'get_energy_incentives' by covering international scope.

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 explicitly says 'Use whenever a user asks what rebates, tax credits, or utility programs apply to solar, batteries, heat pumps, or efficiency work.' It provides clear context for when to use, but does not explicitly mention when not to use or alternatives among siblings, though the worldwide vs US distinction implicitly guides.

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?

Annotations are absent, so the description must convey behavioral traits. It mentions triggering autopilot, a notable side effect, but fails to disclose whether the action is destructive, reversible, or requires authorization. Details about the finalization process itself are missing.

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 exceptionally short with two distinct clauses. While it could benefit from structured presentation (e.g., bullets), every sentence provides unique information without 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?

For a one-parameter tool with no output schema, the description is incomplete. It omits the meaning of assessmentId, what happens after finalization (beyond autopilot), and the response format. The '[free]' note is useful but insufficient.

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 no meaning to the single parameter 'assessmentId'. With 0% schema description coverage, the agent receives no guidance on the parameter's purpose, format, or source. This is a critical gap.

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's action 'Finalize assessment' with a specific verb and resource. It also adds context 'triggers autopilot' which distinguishes it from sibling tools like create_energy_assessment or answer_energy_assessment_question. The purpose is unmistakable.

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 no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., assessment must exist) or situations where it should not be used. The '[free]' hint is cost-related, not usage context.

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 only mentions 'Free' and 'Start a new assessment session,' with no disclosure of side effects, authentication needs, or what happens after creation. This is insufficient for a state-changing action.

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 very short (one sentence) and to the point. It is efficient but could benefit from slightly more context without becoming verbose.

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 parameters and no output schema, the description is adequate for a simple action. However, it does not explain what a session entails or how it relates to sibling tools, leaving gaps in the overall workflow understanding.

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 has zero parameters, so schema description coverage is 100%. The description adds no parameter info, but there are none to document. Baseline 4 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 states 'Start a new assessment session,' which is a specific verb+resource. It distinguishes from sibling tools that involve answering questions or generating reports, but does not explicitly differentiate itself.

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?

No guidance on when to use this tool versus alternatives like answer_energy_assessment_question or complete_energy_assessment. The description lacks context about prerequisites or workflow order.

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 bears full burden. Only discloses price and payment direction; lacks details on side effects (e.g., creating Stripe session), idempotency, required prior steps (e.g., assessmentId must exist), or auth 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?

Very concise single sentence with '[free]' tag, but excessive brevity sacrifices parameter and usage context. No bullet points or structure; front-loaded with purpose but missing organized details.

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?

Lacks output schema, annotations, and parameter descriptions. Does not mention prerequisites (e.g., existing assessment from create_energy_assessment) or expected response format beyond the URL. For a tool in a workflow, this is insufficient.

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 description adds no meaning beyond schema. Both 'email' and 'assessmentId' are unexplained; agent cannot infer what assessmentId refers to or why email is optional.

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?

Clearly states it gets a Stripe Checkout URL for the $19 paid roadmap, distinguishing it from the free roadmap tool (get_energy_node_roadmap) in the siblings list. The verb 'Get' and resource 'Stripe Checkout URL' are specific.

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?

Implies use when user wants to pay $19 for the roadmap (end user pays Viridis directly). Lacks explicit 'when not to use' or alternative names, but sibling 'get_energy_node_roadmap' provides context for free version.

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 discloses 'Honest-range', '± band', 'with assumptions', and '[free — no API key required]'. It also mentions that non-US estimates use a default solar resource. However, it does not detail the assumptions or limitations further.

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, with the main purpose front-loaded. Every sentence adds value with no redundancy or 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?

Given no output schema, the description mentions 'kWh/year ± band, with assumptions' providing some insight into return format. It is complete enough for a free tool, though it could describe the output structure more precisely.

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%, but the description adds valuable context beyond the schema: for systemKw it notes 'Omit to have a size recommended from the bill'; for country it explains non-US behavior; for zipCode it clarifies US vs other formats. This enhances understanding.

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 estimates annual solar production with a range and assumptions, specifying inputs (ZIP code, system size or bill). It distinguishes itself from siblings like check_incentives and match_installers by focusing on production estimation.

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 explicitly says 'Use to sanity-check installer quotes or size a system before talking to anyone,' providing clear context. It also notes the two input modes (systemKw or monthlyBillUsd) but does not explicitly state when not to use it.

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 must disclose behavioral traits. It mentions 'free-tier preview' suggesting limitations, and output content (ranges, next best action), but does not state whether it is read-only, idempotent, or has any side effects. Missing safety/reversibility info.

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 extremely short (one phrase plus pricing), which is concise but under-specified. It lacks structure and clear sentences, sacrificing informativeness. Every word should earn its place, but here it fails to convey essential details.

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 one required parameter, no output schema, no annotations, and many sibling tools, the description is incomplete. It does not explain how to obtain 'assessmentId', what the output format looks like, or what 'ranges' means. Pricing alone does not suffice.

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 has one parameter ('assessmentId') with 0% description coverage. The description adds no meaning to this parameter, failing to specify its format, source, or purpose. Without compensation, the agent has no guidance on what to pass.

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 it generates a 'preview' with 'ranges, next best action', clearly indicating it provides a summary of recommendations. It distinguishes from sibling tools like 'check_incentives' or 'get_node_score' by being a preview, but lacks specificity on what 'ranges' and 'next best action' entail.

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?

No guidance on when to use this tool vs alternatives. The only contextual hint is the cost ($0.05/call), which implies it might be a lightweight option, but no explicit when/when-not conditions or exclusions are provided.

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. It only discloses the cost ($0.25 per call), which is a behavioral trait. However, it fails to state whether the tool is read-only, destructive, or has any side effects. It does not mention authentication requirements, rate limits, or latency. The description is insufficient for the agent to understand the tool's behavior beyond cost.

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 extremely concise at eight words, with no redundancy. However, conciseness should not come at the cost of clarity. The structure is adequate but leaves major gaps in understanding. Every sentence provides value (purpose and cost), but the overall content is insufficient.

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 has one parameter, no output schema, and no annotations, the description is notably incomplete. It does not explain what a 'bound report' is, what the output contains, or any prerequisites (e.g., must have an existing energy assessment). The cost info is helpful but not enough for complete situational understanding.

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 has one parameter 'assessmentId' with no description and 0% coverage. The description does not explain what 'assessmentId' is, how to obtain it, or its format. The addition of 'Property-specific' hints that the assessmentId is for a property, but no concrete guidance is given. The description fails to add meaningful semantics beyond the parameter name.

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 'Property-specific dI/dt analysis' clearly indicates the tool performs a specific technical analysis on a property. While the term 'dI/dt analysis' is domain-specific, it provides a clear verb and resource. It distinguishes from siblings like 'get_eta_i_metric' which might be a different metric. However, the explicit link to generating a 'bound report' is not stated, only implied by the tool name.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, context, or exclude scenarios. For example, it doesn't indicate whether it should be used before or after other tools like 'estimate_production' or 'get_eta_i_metric'. This leaves the AI agent without decision-making context.

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, and the description gives no behavioral details such as side effects, read-only nature, or rate limits. It only mentions pricing, not behavior.

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 very short but cryptic and unhelpful. It includes pricing in a confusing format and lacks front-loaded purpose.

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 tool with no output schema and two parameters, the description fails to explain the tool's purpose, parameters, or return value. It is completely inadequate.

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 2 parameters (limit, offset) with 0% description coverage, and the description does not explain them. The agent gets no help understanding what these parameters do.

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 noun phrase 'Anonymized Energy Node profiles' but lacks a verb, so it doesn't clearly state what the tool does. The name suggests sampling, but the description is vague and does not explicitly say 'get a sample'.

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?

No guidance on when or why to use this tool versus its many siblings. The only note is pricing, which is not usage advice.

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 full disclosure burden but only mentions cost ($0.02/call) and data source (DSIRE). It does not specify read-only nature, authorization needs, or any side effects, leaving behavioral traits unclear.

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 extremely concise with two sentences and a cost note. While it conveys core purpose efficiently, it sacrifices informative detail, but the structure is front-loaded and uncluttered.

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, no annotations, and incomplete parameter explanation, the description fails to fully contextualize the tool. Missing return format, parameter interplay, and usage constraints make it inadequate for informed 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 0%, so description must explain parameters. It partially addresses 'zipCode' through context, but 'assessmentId' is entirely unexplained. The description does not add meaning beyond the schema for this parameter.

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 'State/utility incentive checklist by ZIP (DSIRE-grounded)', identifying the verb (get), resource (incentives), and scope (by ZIP). However, it does not explain the assessmentId parameter or differentiate from the sibling 'check_incentives', which could confuse agents.

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?

No guidance is given on when to use this tool versus alternatives like 'check_incentives' or other listed tools. The description lacks context for appropriate usage scenarios or exclusions.

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?

The description adds behavioral context about cost ($0.10 per call) and a prerequisite (payment), which are beyond the name. However, it does not disclose whether the tool is read-only, what happens if payment is not made, or any side effects. With no annotations, the description partially compensates but lacks important behavioral details.

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 very short, consisting of two sentences and a price note. It avoids unnecessary words. However, it sacrifices informativeness for brevity.

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 simple schema (one parameter, no output schema) and the complexity of the domain (energy roadmap), the description is incomplete. It does not explain what the roadmap contains, the format of the output, or the meaning of 'unlocked'. The payment condition introduces ambiguity about success conditions.

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 has a single parameter 'assessmentId' with 0% description coverage. The tool description does not explain what this parameter represents or how to obtain it, leaving the agent without necessary context to fill it correctly.

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 'Full unlocked roadmap (after end-user $19 payment)' is vague about what the tool does. It does not clearly state that this tool retrieves a roadmap; the verb 'get' is implied from the name but not explicit. The mention of payment is more about business logic than functionality, making the purpose unclear.

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?

No guidance is provided on when to use this tool versus siblings like 'get_energy_node_score' or 'get_guide'. The payment prerequisite is mentioned but without context of when it should be satisfied or alternatives if not paid.

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 disclose behavior. It only mentions cost per call, but fails to indicate whether the tool is read-only, its side effects, or data format. Inadequate for a tool without annotation support.

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?

Brief but at the expense of completeness. The description is minimal, missing critical details. While not verbose, it fails to convey necessary information, so conciseness is not beneficial.

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 no output schema, no param descriptions, and related siblings, the description is severely lacking. It does not provide enough context for an AI agent to invoke it correctly or understand its output.

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?

With 0% schema description coverage, the description must explain the 'assessmentId' parameter. It does not: no hint on what it is, its format, or where to obtain it. User is left uninformed.

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 states '7-axis Energy Node Score breakdown', indicating the tool provides a score breakdown. However, the meaning of '7-axis' is unclear, and the purpose is vague. It does not distinguish from sibling tool 'get_node_score'.

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?

No guidance on when to use this tool versus alternatives like 'get_node_score' or 'get_eta_i_metric'. The description only mentions cost but no context for tool selection.

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, and the description adds minimal behavioral context. It mentions 'Free' implying no cost, but does not disclose rate limits, data freshness, idempotency, or other traits.

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 short but includes redundant '[free]'. It is generally concise but could be more informative without adding length.

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 simplicity of the tool (one optional parameter, no output schema), the description is incomplete. It fails to explain the metric's return format, how 'days' affects results, or any other usage details.

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 only parameter 'days' is not mentioned in the description. With 0% schema coverage, the description completely fails to explain its purpose or valid range.

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 identifies the resource as a public metric, clearly distinguishing it from sibling tools like get_energy_node_score. However, 'intelligence-efficiency metric' is somewhat vague and does not specify what the metric represents.

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?

No guidance on when to use this tool vs alternatives. The description only states it is 'Public' and 'Free' but does not provide context for appropriate usage scenarios.

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 transparency burden. It discloses the tool is free and requires no API key, and emphasizes the content is grounded and citable. It does not mention any destructive or write behavior, which is appropriate for a read-only retrieval tool.

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, comprising two sentences that efficiently convey purpose, content details, usage notes, and cost. No extraneous 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?

Given the tool has no output schema, the description adequately explains what the guide contains and its purpose for answering incentive questions. It could optionally mention pagination or size limits but is sufficient for a retrieval 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 description coverage is 100% for the single 'slug' parameter. The description adds value beyond the schema by specifying that the slug must be exactly as returned by list_guides and provides an example, aiding correct invocation.

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 retrieves the full text of one EnergyAI incentive guide by slug, listing its components (intro, sections, FAQs, primary sources). This distinguishes it from sibling tools like list_guides (which lists guides) and answer_energy_assessment_question (which answers questions).

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 notes that the tool is free and requires no API key, and advises to cite the canonical URL when quoting. It implicitly indicates usage when a specific guide slug is known from list_guides, but does not explicitly state conditions for use vs. alternatives.

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 must fully disclose behavior. It mentions cost, which is good, but fails to mention side effects, read-only nature, or output structure, leaving behavioral 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 very short, which is concise, but it sacrifices necessary detail. It is front-loaded with the purpose but is not optimally structured for clarity.

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 required parameter and no output schema, the description is incomplete. It omits parameter semantics, return format, and usage context, leaving the agent underinformed.

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 does not explain the lone parameter 'assessmentId'. No added meaning 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 states it ranks upgrades by 'intelligence-bound lift per dollar', giving a specific metric, but the terminology is jargon and not immediately clear. It distinguishes somewhat from siblings but lacks explicit 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?

No guidance on when to use this tool vs. alternatives like 'generate_energy_recommendation_preview'. The only additional info is cost, which is not usage 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 are provided, so the description carries the burden. It discloses that the tool is free and requires no API key, and that it provides an instant score based on property facts. However, it lacks details on rate limits, data persistence, or any 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 a single sentence with a list of axes and a note about inputs. It is concise and front-loaded with the key output, though it could be slightly more 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?

Given the 12 optional parameters and no output schema, the description clearly explains the output (score + next action) and mentions the 7 axes. It provides adequate context for an AI agent to decide to use it, though it could elaborate on the 'highest-leverage next action'.

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?

With 100% schema description coverage, the schema already documents all parameters. The description adds no additional parameter-level detail beyond summarizing the output, so baseline 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 states it returns an 'Instant Energy Node Score (0–100 across 7 axes)' plus a 'single highest-leverage next action', which is specific and differentiates from siblings like 'get_energy_node_roadmap' or 'estimate_production'.

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 mentions 'More inputs → tighter score' and that it's free with no API key, but does not explicitly state when to use this tool versus alternatives like 'complete_energy_assessment' or 'generate_energy_recommendation_preview'.

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, description adds useful behavioral context: no consent collection required, free, no API key required. Does not mention rate limits or side effects, but covers key differentiators.

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, zero waste. Key information (purpose, when to use, alternative) is front-loaded. Square brackets add no extra cost.

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, description mentions output type ('ready-to-share link'). All 3 parameters are documented in schema. Tool is simple and description covers what agent needs to know.

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 covers 100% of parameters with descriptions and examples. Description adds no additional meaning for parameters beyond what schema provides. Baseline 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 states it converts a conversation into a real installer quote and returns a ready-to-share link. It uses specific verb 'returns' and resource 'link', and distinguishes from sibling route_lead.

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?

Explicitly states when to use this tool ('by default when a homeowner wants next steps') and when to use alternative route_lead ('only if you already have their explicit consent captured'). Provides clear decision criteria.

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 the full burden. It adds valuable behavioral context: the tool is free, no API key required, and each entry includes a canonical URL for citation. This is useful for an agent deciding whether to invoke the tool.

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 at two sentences plus a bracketed note. It front-loads the key purpose and includes a clear call to action. Could be slightly more structured, but efficient overall.

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 exists, and the description only hints at return structure (includes canonical URL). Missing details on pagination or full response format. Given 3 optional parameters, description could provide more completeness.

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 baseline is 3. The description does not add significant new meaning beyond the schema: it mentions state-level and federal guides, but the schema already describes region. No additional details on limit or topic.

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 provides an index of source-cited, 2026-accurate US home-energy incentive guides by state, with specific examples (solar, heat pumps, batteries, weatherization). It distinguishes itself from sibling tool get_guide by noting that list_guides is for indexing and get_guide is for fetching full text.

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 advises using list_guides to 'ground answers about what incentives exist in a state, then fetch the full text with get_guide.' While it doesn't explicitly state when not to use it, it provides clear context and a direct link to an alternative tool.

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 convey behavioral traits. It discloses pricing ($0.05/call) and a result limit (up to 3 matches), but fails to mention if the tool is read-only, idempotent, requires authentication, or what happens on errors. The description is insufficient for an agent to understand 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 very short (one sentence plus pricing note), but it front-loads the key action. However, it sacrifices completeness for brevity, so it is not optimally concise—it leaves out essential 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?

Given no output schema and simple parameters, the description should cover return format, error scenarios, and use cases. It only hints at the output count and cost, leaving major gaps. The tool's place among 20 siblings demands more context.

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%, yet the description adds no meaning to the parameters. It mentions 'region' but does not explain that zipCode and state define it, nor does it clarify contractorCategory. The agent gets no help in selecting or formatting parameter 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 states 'Up to 3 installer matches in a region', which implies the tool matches installers, but it does not specify the domain (e.g., solar, energy) or distinguish from sibling tools like 'route_lead' or 'submit_contractor_match_request'. The purpose is vaguely clear but lacks specificity.

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 alternatives. The description only mentions region and pricing, with no context about prerequisites, constraints, or when not to use it.

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?

Without annotations, the description is the sole source of behavioral information. It only mentions a cost of $0.10 per call but does not disclose whether the tool is read-only, modifies data, requires authentication, or what the effects are.

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 front-loaded, but it omits essential information such as the output format or behavioral details, making it too minimal for a tool with no annotations or output schema.

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 absence of annotations and output schema, the description is incomplete. It fails to explain what the tool returns, how to interpret results, or any constraints. The tool's complexity is low but still requires more context.

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?

With 50% schema description coverage, the description adds little beyond the schema. The 'quoteText' parameter is already described in schema, but 'assessmentId' is left unexplained. The description does not clarify the purpose of either parameter.

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 verb 'benchmark' and the resource 'installer quote', making it distinctive from sibling tools which focus on energy assessments, production estimates, and other tasks.

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?

No guidance is provided on when to use this tool versus alternatives, nor are there any prerequisites or exclusions mentioned. The cost note is helpful but does not constitute usage 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 discloses consent requirements and return value, but omits side effects, data handling, error scenarios, or routing process details.

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 concise sentences cover purpose, requirement, and return; minor improvement possible by front-loading the consent requirement.

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?

Considering 14 parameters and no output schema, the description is adequate but lacks details on response structure beyond leadId and error handling.

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 high (71%), and the description adds context about consent text sourcing but does not significantly enhance understanding 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 it submits a consented homeowner project and routes an installer, with a leadId return. However, it does not explicitly distinguish from sibling tools like match_installers.

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 emphasizes required consent and free usage, but lacks guidance on when to use this tool over alternatives or prerequisites beyond consent.

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; description only reveals it is free and requires consent, but lacks details on side effects (e.g., submission creates a lead), authorization requirements, or response behavior.

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?

Very concise, two sentences plus tag, no wasted words. However, could benefit from a structured list of parameters or usage steps.

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?

With 7 parameters, no output schema, and several sibling tools, the description lacks context on prerequisites (e.g., existing assessment), error handling, and return value format. 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 only 14% (only consentText described). Description mentions consentText and consentTimestamp but adds no meaning for 5 other parameters (assessmentId, contactName, contactEmail, contactPhone, consentVersion).

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 'Submit a consented installer lead' with verb and resource, and 'FREE' and affiliate model distinguish it from siblings like match_installers which likely perform different matching functions.

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?

No explicit guidance on when to use this vs alternatives like match_installers; only implies consent is required but does not clarify conditions or exclusions.

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