BB diffraction-scatter
Use this skill for diffraction / scattering data processing with pyFAI. It covers the full workflow: calibration (generating .poni files), azimuthal integration (1D/2D), batch processing, GIWAXS/Fiber maps, chi/azimuthal profiles, sector integration, full 2D cake maps, large HDF5/Eiger workflows, uncertainty/error-model aware integration, mask/dark/flat/polarization corrections, and installation help for Python & pyFAI. Trigger this skill whenever the user asks about any of the following tasks: - Calibration (creating or using a .poni file) - 1D/2D integration, batch integration, streaming - GIWAXS, qip/qoop, azimuthal/chi profiles, sector, cake - Error models, corrections (mask, dark, flat, polarization) - Installing or using pyFAI (Having a .poni file is a normal step in the workflow, not a prerequisite for using this skill.) --- 使用本技能处理衍射/散射数据（基于 pyFAI），覆盖完整工作流： 标定（生成 .poni 文件）、方位角积分（1D/2D）、批处理、GIWAXS/Fiber 图、 χ 积分、扇区积分、2D cake 图、大规模 HDF5/Eiger 数据处理、带误差模型的积分、 mask/dark/flat/偏振校正，以及 Python/pyFAI 安装帮助。 只要用户询问以下任一任务，即可触发本技能： - 标定（创建或使用 .poni 文件） - 1D/2D 积分、批处理、流式处理 - GIWAXS、qip/qoop、方位角/χ 剖面、扇区、cake - 误差模型、校正（mask、dark、flat、偏振） - 安装或使用 pyFAI （.poni 文件是工作流中的正常环节，并非使用本技能的前提条件。）
As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, progress reporting
How to improve
- Shorten the description to 1024 characters.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1201 chars, limit 1024
Process rating: all ten parameters 68/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Failures and branches. 4 branches
- 100Steps. 48 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2459 tokens
- 100Running it twice. No mutating operations
- low 13 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1200: 120–800 characters recommended
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +4Structure: 21 headings
- +3Step-by-step instructions: 48 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.