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run_spfc

Calibrate spectrophotometric flux on linear, plate-solved images, writing the flux metadata that run_mgc requires. Specify mono or color filter curves for accurate calibration.

Instructions

Run SpectrophotometricFluxCalibration: writes the flux metadata that run_mgc requires. The image must be plate-solved and linear. Needs the camera QE curve (default "Ideal QE curve"; pass qe_name for the real sensor, see find_filters) and the filter curve. MONO image: pass filter (L, R, G, B, Ha, OIII, SII) and optionally filter_name (a measured curve from the database; otherwise a flat passband from wavelength_nm/bandwidth_nm is used). COLOR image: omit filter and pass red_filter_name, green_filter_name, blue_filter_name (otherwise flat R/G/B passbands).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoMono only. One of L, R, G, B, Ha, OIII, SII
qe_nameNoCamera QE curve name (default "Ideal QE curve")
view_idYesView ID to calibrate
filter_nameNoMono: measured filter curve name from find_filters
bandwidth_nmNoMono: filter bandwidth in nm, if filter_name is not given
wavelength_nmNoMono: filter center wavelength in nm, if filter_name is not given
red_filter_nameNoColor: measured R filter curve name from find_filters
blue_filter_nameNoColor: measured B filter curve name from find_filters
green_filter_nameNoColor: measured G filter curve name from find_filters

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden, and it discloses that the tool writes metadata, has prerequisites, uses a default Ideal QE curve, and falls back to flat passbands when no measured filter curve is given. It does not mention overwrite/idempotency or possible failure modes, which keeps it slightly below a 5.

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?

Three dense sentences front-load the purpose before prerequisites and options. Every clause carries information, and the MONO/COLOR split makes a 9-parameter tool navigable without redundancy.

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

Completeness4/5

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

For a 9-parameter tool with no annotations or output schema, this is unusually complete: it covers prerequisites, dependencies, parameter selection rules, and defaults. The only gap is the absence of any statement about return values, overwriting existing metadata, or failure behavior.

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 coverage is 100%, but the description goes beyond the schema by explaining the MONO vs COLOR parameter family, the rule to omit filter for color images, and the flat-passband default when filter_name is absent. This is meaningful semantic guidance that cannot be fully inferred from the property descriptions alone.

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?

States an action verb 'Run' with the expanded resource SpectrophotometricFluxCalibration and the concrete effect 'writes the flux metadata that run_mgc requires.' This distinguishes it from sibling calibration tools by naming its downstream consumer, so an agent can tell what it does and why.

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

Usage Guidelines5/5

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

Gives explicit prerequisites ('must be plate-solved and linear'), required inputs (QE curve, filter curve), and a branching rule for mono vs color images. It also routes the agent to find_filters for curve names and positions this as the step before run_mgc, providing clear when-to-use context.

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