voltcast

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

With no annotations provided, the description carries full burden for behavioral transparency. It fails to disclose whether the tool is read-only, what happens if no window is found, authentication requirements (though 'Pro+' hints at tiers), rate limits, or side effects. The description only hints at the data source but lacks depth.

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, well-structured sentence that conveys the core idea without redundancy. It is front-loaded with the primary action. However, it could be slightly more informative without sacrificing conciseness, e.g., by mentioning the output (returned windows) or input constraints.

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 5 parameters, no output schema, and no annotations, the description is insufficient for an agent to fully understand usage. The description does not explain return format, edge cases, or how to interpret the results. The agent lacks context for error handling or expected output 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?

The input schema has only 40% parameter description coverage (count and duration_minutes have descriptions; to, from, zone do not). The tool description adds no additional parameter details, leaving the undocumented 'to', 'from', and 'zone' parameters ambiguous. While 'zone' might be inferred from the context of geographic zones, the description does not clarify date range parameters or how 'count' interacts with the search algorithm.

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 purpose: 'Find the cheapest contiguous time window(s) to run a load, over published prices + forecast (Pro+).' It specifies a verb (find), resource (cheapest contiguous time windows), and context (prices, forecast, Pro+ tier). It effectively distinguishes itself from sibling tools like get_prices (which only retrieves raw prices) and get_forecast (which only retrieves forecasts).

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 lacks any guidance on when to use this tool versus alternatives. It does not mention preconditions (e.g., need for Pro+ tier), exclusion criteria (e.g., when raw price data is needed), or conditions where the tool might not be appropriate. No explicit when-to-use or when-not-to-use hints 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?

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions the derived nature of the data but omits details like authentication, rate limits, or whether the data is cached.

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 no extraneous words, but it is too brief to convey necessary information. It achieves conciseness at the expense of completeness.

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 lack of output schema, annotations, and parameter coverage, the description is insufficient for an agent to use the tool correctly. It does not describe input usage or output structure beyond a high-level summary.

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 any parameter semantics. It fails to clarify what 'zone', 'to', or 'from' represent, leaving the agent to infer meaning from names alone.

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 defines the tool's output: carbon intensity and green score from the live generation mix. While it doesn't explicitly differentiate from sibling tools like get_renewables, the resource is distinct enough that an agent can infer its purpose.

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 get_renewables or get_forecast. The description lacks context about prerequisites or typical use cases.

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

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

With no annotations provided, the description carries the full burden. It discloses the probabilistic nature, tiers (Pro+ feature), and a source for accuracy verification. This goes beyond the basic name, though details like response format or rate limits are omitted.

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 with no fluff. Every word adds value: title, probabilistic nature, tiers, horizon, and accuracy reference.

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 (2 params, no nested objects, no output schema), the description provides adequate context for invoking the tool. It covers purpose, key parameters implicitly, and an external reference. Minor improvement could be to explicitly define the zone parameter.

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 0% description coverage, so the tool description must compensate. It partially adds meaning by linking 'up to 7 days ahead' to the horizon parameter, and 'price forecast' implies zone is a location. However, it does not define the zone parameter explicitly or list the enum values, leaving some gaps.

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 is a 'Probabilistic price forecast' tool, specifying the output (P50 curve, P10/P90 on Pro+) and the time horizon (up to 7 days). This distinguishes it from siblings like get_prices (likely current prices) and other data tools.

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 implicitly suggests use for price forecasting by mentioning the forecast horizon and accuracy reference. However, it does not explicitly state when to use this tool versus alternatives like get_prices or cheapest_window, nor does it mention prerequisites 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, the description adds context about the day-ahead nature and native resolution, but lacks details on rate limits, data completeness, error behavior, or any side effects. It provides some transparency but not comprehensive.

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 concise — two sentences with no redundancy. It front-loads the core purpose and includes critical prerequisite (API key) efficiently.

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?

While the description covers the main purpose and a key prerequisite, it omits information about the return format, pagination, date range handling, or error scenarios. For a tool with 4 parameters and no output schema, more context would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes 3 of 4 parameters well (to, from, zone). The description does not add further parameter-specific info beyond listing units for prices. Given high schema coverage, baseline 3 applies.

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 'Day-ahead electricity prices (EUR/MWh, 15-minute native) for a bidding zone', specifying the output unit and resolution. It distinctively separates this tool from siblings like 'cheapest_window' or 'get_carbon' by focusing explicitly on prices.

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 the API key requirement with a link, which is a prerequisite for use. However, it does not provide guidance on when to choose this tool over alternatives, nor does it specify any conditions 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, the description carries the full burden. It discloses data sources (TSO, Voltcast model volt-res-1), statistical bands (q10-q90), and verification (head-to-head comparison). However, it does not mention update frequency, caching behavior, or any limitations, leaving minor gaps.

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

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

The description is a single, efficient sentence that front-loads the core purpose. It packs substantial information without being verbose, though the list at the end is slightly dense. Every part serves a 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?

Given the complexity (3 parameters, no output schema, no annotations), the description adequately covers what the tool returns (forecasts, bands, realizations, verification). It mentions usage contexts (Pro/Scale/Balancing/Quant). The absence of output format details is acceptable without an output schema.

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 clear descriptions for each parameter (ISO 8601 start/end, zone code). The description adds context about the data (forecasts, bands, verification) but does not enhance parameter-level meaning beyond what the schema already provides, meeting the baseline for 100% coverage.

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

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

The description clearly states it provides day-ahead wind and solar generation forecasts, specifying the resource (renewable generation) and the verb (get). It distinguishes itself from siblings like get_prices, get_carbon, and get_forecast by mentioning specific data sources (TSO official forecast, Voltcast model) and verification details.

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 day-ahead forecasts but does not explicitly state when to use this tool versus alternatives like get_forecast. It mentions 'Pro/Scale/Balancing/Quant' which hints at user categories but lacks clear when-to-use or when-not-to-use 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 provided, so description carries full burden. It discloses 'No auth required' and implies it lists all supported zones, but lacks details on data freshness, rate limits, or completeness guarantees.

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?

Single sentence that is front-loaded with purpose and key details. 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?

For a parameterless tool with no output schema, the description covers the essential: what it lists (zones with codes, names, capabilities) and that no auth is required. Could mention return format or pagination, but not necessary for such a simple 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?

Tool has 0 parameters with 100% schema description coverage. Baseline is 4; description adds no parameter info but none is needed.

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 verb 'list', the resource 'supported European bidding zones', and the output details 'codes, names, and capabilities'. It distinguishes from sibling tools which focus on prices, forecasts, etc.

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 'No auth required', indicating ease of use. Does not explicitly state when not to use or provide alternatives, but for a simple list tool, the context is clear.

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