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calculate_solar_panel_output

Estimate solar panel daily and yearly energy output by location and system size. Use for solar installation sizing. Inputs: kW capacity, latitude, panel orientation, shading %. Returns kWh/day and kWh/year. See list_bundles for related 'energie' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
area_m2NoPanel surface area in m2 (optional, informational)
panel_watt_peakYesTotal peak power of the installation in Watts (Wp)
hours_sun_per_dayNoAverage peak sun hours per day (default 4)
efficiency_loss_pctNoSystem efficiency loss percentage (default 15%)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3/5.0
Behavior2/5

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

No annotations provided, so description bears full burden. It does not disclose any behavioral traits, constraints, or side effects beyond 'estimate'. The mismatch between described and actual inputs further obscures behavior.

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

Conciseness4/5

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

Description is brief with three short sentences, front-loading purpose. However, the third sentence listing inputs is unnecessary and inaccurate, slightly reducing conciseness but not severely.

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

Completeness3/5

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

Covers purpose and outputs (kWh/day, kWh/year). With output schema present, return values are documented elsewhere. However, missing guidance on location parameter (not in schema) and defaults for sun hours and efficiency loss, leaving gaps for correct invocation.

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

Parameters2/5

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

Schema coverage is 100% with clear descriptions, so baseline is 3. However, description adds no semantic value; it inaccurately lists inputs not in schema (latitude, orientation, shading) and omits actual parameters like hours_sun_per_day and efficiency_loss_pct, potentially confusing agents.

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

Purpose4/5

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

Clearly states the tool estimates solar panel energy output by location and system size, with specific outputs. Differentiates from siblings by mentioning related 'energie' calculators. However, description inaccurately lists inputs (kW capacity, latitude, orientation, shading %) that do not match the actual schema, which reduces clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Advises use for solar installation sizing and points to list_bundles for related tools, providing some context. Lacks explicit when-not-to-use or alternatives, but sufficient for a calculator among many siblings.

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

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