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akontadakis
by akontadakis

spectral_epw

Generate spectral sky data from EPW files, enabling year-long or hourly spectral analysis with configurable aerosol, cloud, and ozone models.

Instructions

Emit spectral-sky artifacts from an EPW over the year (or hours). LONG-RUNNING for a full year.

forms ⊆ {spd_set, band_matrix, spectral_wea, sidecar} (default all). Writes into work_dir and returns {files: {form: path}, n_records}. hours is a list of [month, day, hour] to subset. engine: spectrl2 (default) | smarts (requires SMARTSPATH).

Opt-in refinements (defaults reproduce prior output): ozone_mode='climatology' computes ozone from the EPW LOCATION lat/lon + date (van Heuklon 1979); aerosol_g overrides the 0.65 asymmetry; aod_anchor_nm converts a declared-wavelength AOD (e.g. 550) to tau500 via the Angstrom exponent. smarts_aerosol (engine="smarts" only): None/"rural" (default) or "user" to make the Ångström exponent + asymmetry factor settable via the SMARTS Card 8 USER aerosol model. cloud_variant: which SEDES1 cloud CCM to apply to the sky-diffuse spectrum — 'reanchored' (default, byte-identical to omitting this arg) | 'verbatim' (faithful Fig.11 CCM) | 'seed' (legacy eyeballed 9-anchor seed) | 'local' (your own locally-fitted CCM, requires ccm_coeffs). ccm_coeffs: path to a fitted CCM CSV (from sedes1_fit) — required when cloud_variant='local'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
epwYes
formsNo
hoursNo
engineNospectrl2
work_dirNo
aerosol_gNo
ccm_coeffsNo
ozone_modeNo
aod_anchor_nmNo
cloud_variantNo
smarts_aerosolNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It discloses that the tool is long-running for a full year, writes to work_dir, returns a structured output, and that certain defaults reproduce prior output. It also flags engine-specific requirements (e.g., SMARTSPATH for smarts) and dependency on ccm_coeffs for 'local' cloud variant.

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

Conciseness5/5

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

The description is dense but well-structured, using a top-line purpose statement followed by detailed parameter explanations separated by line breaks. Every sentence provides essential information without redundancy, and the main purpose is front-loaded before the parameter details.

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

Completeness5/5

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

Given the tool's complexity (11 parameters, output schema present), the description is remarkably complete. It covers the purpose, output format, parameter semantics, dependencies, defaults, and variations. There are no obvious gaps that would prevent an agent from calling the tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must explain all parameters. It does so comprehensively: forms, hours, engine, work_dir, ozone_mode, aerosol_g, aod_anchor_nm, smarts_aerosol, cloud_variant, and ccm_coeffs are all explicitly defined with their semantics and defaults. This fully compensates for the missing schema descriptions.

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

Purpose5/5

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

The description clearly states a specific verb ('emit') and resource ('spectral-sky artifacts from an EPW'), with explicit mention of forms and the annual/hourly scope. It differentiates from sibling tools like spectral_sky_from_epw by focusing on emitting artifacts and the option set, so an agent can infer its role.

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?

The description provides context about long-running behavior and various configuration options, but it does not explicitly state when to use this tool versus alternatives like spectral_sky_from_epw or atmosphere_from_epw. The intended usage is implied by the tool's purpose rather than explicitly contrasted.

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