VoltPlan Wiring Diagrams

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

With no annotations, description carries full burden. It correctly indicates the tool is a calculator returning results, but does not mention if it has side effects, authentication needs, or any assumptions about input ranges. The output format is briefly described but lacks detail on data types or structure.

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?

Three sentences, no wasted words. First sentence states purpose and output, second adds key factors, third lists return items. Front-loaded with main action, 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?

Given 6 parameters and no output schema, description explains inputs and outputs adequately. It references a dependency on another tool (calculate_power_budget) and covers key assumptions. However, it could be more complete by specifying units for output or constraints on wiring configuration format.

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 baseline is 3. Description adds context by summarizing how parameters (daysOfAutonomy, depthOfDischargePercent) are used together, but does not add new meaning beyond what schema already provides for each parameter individually.

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 specific verb 'calculate' with resource 'battery bank size' and mentions inputs and outputs. It clearly distinguishes from sibling tools like calculate_power_budget or calculate_solar_size by focusing on battery bank sizing alone.

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?

Description implies usage after calculate_power_budget by referencing 'daily energy consumption (from calculate_power_budget)', but does not explicitly state when to use this vs other battery-related tools like calculate_battery_config. No exclusion or alternative 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 full burden. It lists outputs but does not disclose behavior for edge cases (e.g., unachievable voltage combinations) or error handling. A minimal acceptable score given the calculator nature.

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, front-loaded sentence that efficiently conveys purpose and outputs. No redundant words; 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?

Given no output schema, the description adequately covers return values. It mentions number of batteries, wiring configuration with an example (2S3P), and instructions. Could specify format but sufficient for a simple calculator.

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 description adds no additional meaning to the parameters. It does not elaborate on how parameters are used or provide examples 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 uses a specific verb 'determine' and explicitly names the resource (battery arrangement) and outputs (number of batteries, wiring config, instructions). This clearly distinguishes it from sibling tools like calculate_charging_time or calculate_inverter_size.

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 such as calculate_battery_bank or generate_wiring_diagram. It does not mention any prerequisites, limitations, 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the two charging phases (bulk and absorption) and that it works across charging sources. This provides useful context beyond the input schema, though it could mention assumptions like ideal battery behavior or temperature 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 long, front-loaded with the main purpose, and every sentence adds necessary information. There is no fluff 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?

Despite the lack of an output schema, the description adequately explains the tool's behavior and inputs. It covers the key phases and source flexibility. It could be more complete by specifying output format (e.g., returns hours) or mentioning limitations, but it is sufficient for a calculator 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?

The schema covers 100% of parameter descriptions, so baseline is 3. The description adds value by explaining the charging phases, which gives context to the parameters (e.g., why targetSoC above 80% behaves differently). This goes beyond the schema's simple descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool estimates charging time for a battery bank from a given state of charge to a target level. It uses a specific verb ('Estimate') and resource ('charging time'), and distinguishes itself from sibling calculators (e.g., calculate_battery_bank, calculate_solar_size) which focus on other aspects of system design.

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 states it works for any charging source (solar, shore power, alternator), providing clear context for when to use. However, it does not mention when not to use it or suggest alternative tools, though none of the siblings appear to duplicate this functionality.

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; the description adequately discloses key behaviors (surge handling, 25% headroom, computed outputs) for a non-destructive calculator.

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 compact sentences with no wasted words; front-loaded with core 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?

Covers inputs, calculation assumptions, and outputs; missing edge case handling but sufficient for a simple calculator 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%, so description adds limited value beyond schema; it explains how parameters are used in calculation but no new semantic detail per 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 tool calculates recommended inverter size for AC loads from a DC system, accounting for continuous power, surge, and headroom, and distinguishes it from sibling tools like calculate_battery_bank.

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 inverter sizing but lacks explicit when-to-use or when-not-to-use guidance relative to siblings.

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 exist, so description carries full burden. It describes the calculation and outputs (Wh/Ah, peak power, average power). For a pure calculation tool, this is adequate, though it could mention that it has no side effects (read-only).

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: first states the purpose, second gives contextual guidance. No wasted words, front-loaded with key 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?

No output schema, but description mentions return values (Wh, Ah, peak power, average power). Missing details on output format, but sufficient for a straightforward calculation tool. Could be improved with example or more precise return structure.

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 description adds value by summarizing parameter usage (power draw, hours, quantity) and outputs, going beyond the schema's individual field descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool calculates total daily energy consumption from electrical loads, specifying inputs and outputs. It distinguishes itself from sibling tools by positioning it as the first step in battery/solar sizing.

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?

Description provides clear context that this is typically the first step in sizing a battery bank and solar system, guiding when to use it. However, it does not explicitly state when not to use it or mention alternatives among siblings.

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 of behavioral disclosure. It explains what the tool accounts for (efficiency losses) but does not mention whether it has side effects, is read-only, or any authentication or rate-limit considerations.

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 long with no unnecessary words. It front-loads the purpose and concisely lists inputs and outputs.

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 3-parameter calculator without output schema, the description covers inputs and general output. However, it vaguely mentions 'common panel configurations' without detailing the output structure, leaving some ambiguity.

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 already describes each parameter with examples and defaults. The description adds context about efficiency losses but does not significantly enhance parameter 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 the tool calculates required solar panel wattage based on daily consumption and peak sun hours. It distinguishes from sibling tools like calculate_power_budget by focusing on sizing panels rather than estimating consumption or battery sizing.

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 when daily consumption is known (from calculate_power_budget) and when peak sun hours are available. However, it does not explicitly state when not to use or mention alternatives among sibling tools.

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?

Discloses key behaviors: considers ampacity and voltage drop, returns resistance, power loss, fuse recommendation, and supports copper conductors from 0.75 mm² to 240 mm². No annotations to contradict, but could mention output format or algorithm assumptions.

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?

Three concise sentences: main action, what it considers, and what it returns. No fluff, well-structured, and front-loaded.

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 complexity of 7 parameters and no output schema, the description provides a good high-level overview. However, it does not specify output format or that it selects from standard cable sizes, leaving some gaps.

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 parameters are well-described in schema. The description adds contextual value by explaining why parameters like temperature and voltage drop are relevant for ampacity and voltage drop calculations.

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 calculates wire gauge for DC circuits, considering ampacity and voltage drop, and returns resistance, power loss, and fuse recommendation. It is distinct from sibling tools like battery or solar sizing.

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 or not use this tool versus alternatives. While sibling tools are different, the description does not provide criteria for choosing this tool over others.

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 effectively discloses key behaviors: auto-generation of protection components when both batteries and loads are provided, and details about output format (SVG vs PNG) with rendering notes. No contradictions.

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 concise: two sentences plus one line of behavioral detail, front-loaded with purpose and return type. Every sentence adds value 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 tool with 5 parameters (1 required) and no output schema, the description covers purpose, return type, output format behavior, and a key auto-generation rule. It is complete for effective 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 coverage is 100%, but the description adds significant value by explaining the auto-generation rule and providing regional voltage guidance for charger input voltage, enhancing parameter 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 the tool generates electrical wiring diagrams for specific contexts (campers, boats, off-grid setups) and distinguishes itself from sibling calculation tools by focusing on diagram generation.

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?

Usage is clear for generating diagrams, but no explicit guidance on when not to use it or comparison with siblings is provided. However, the context makes it evident that this is for diagram output, not calculations.

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 bears full responsibility. It indicates a safe read operation (listing) with no destructive effects. However, it does not mention output format or any potential limits, which is acceptable for a simple listing tool but not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with purpose and followed by usage guidance. Every sentence is essential with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (no parameters, no output schema), the description provides necessary context: what it does and how to use it relative to a sibling. Lacks output format details, but that is a minor omission for a discovery 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?

There are zero parameters, and schema coverage is 100%. The description does not need to add parameter details; baseline score of 4 applies as per guidelines.

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 'List all available component types and example configurations for building wiring diagrams,' specifying the verb and resource. It also distinguishes from the sibling tool generate_wiring_diagram by noting this is a prerequisite for understanding parameters.

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 advises to use this before calling generate_wiring_diagram, providing clear context. However, it does not discuss when not to use it or alternative tools among siblings.

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