# Lattice Dspacing

> Measures d-spacings and fits atomic lattices from high-resolution STEM images using Bayesian inference, reporting posterior intervals for each lattice parameter.

- Skill: `emskills-mcp/lattice-dspacing` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add emskills-mcp/lattice-dspacing`
- Raw SKILL.md: https://api.skillmd.com/api/skills/emskills-mcp/lattice-dspacing/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: BSD-3-Clause
- Author: emskills-mcp (https://skillmd.com/u/emskills-mcp)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/emskills-mcp/lattice-dspacing

---


# lattice-dspacing

## Scope
Measures d-spacings and fits atomic lattices from high-resolution STEM images using Bayesian inference, reporting posterior intervals for each lattice parameter.

Expects standard STEM data products (image stacks, spectra or session
directories as appropriate) with pixel size / dispersion recorded in the file
metadata. Out of scope: acquisition scheduling, sample preparation, and any
analysis outside the reconstruction stage of the workflow.

## Safety
Read-only — no instrument control. The skill reads data from disk and returns results; it never moves the stage, changes dose, or alters column settings.

## Usage
```json
{
  "tool": "fit_lattice",
  "arguments": {
    "input": "/data/stem/session-001",
    "output": "/data/stem/session-001/fit_lattice"
  }
}
```

Returns a JSON object with `ok`, a `result` payload carrying the primary
measurement or map, and `diagnostics` with per-item confidence. Units are SI
unless stated otherwise in the result schema.

## Reproducibility
Runtime: `python 3.10`. Pin dependencies in `requirements.txt` / `package.json`
and run with a fixed seed. Reviewers can reproduce the reported numbers with:

```bash
cd skills/lattice-dspacing
pip install -r requirements.txt && python3 verify.py --fixture fixtures/sample --seed 0
```