Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add learningmatter-mit/AtomisticSkills --skill mat-calphad-phase-diagramgit clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/learningmatter-mit/atomisticskills/mat-calphad-phase-diagram)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/mat-calphad-phase-diagram"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/mat-calphad-phase-diagram.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.00665 |
| Opus 5 | $0.00016 | $0.00332 |
| Sonnet 5 | $0.00007 | $0.00133 |
| Haiku 4.5 | $0.00003 | $0.00067 |
Grade A, and why
mat-calphad-phase-diagram scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mat-calphad-phase-diagram
Goal
To plot macroscopic metallurgical Temperature-composition ($T-x$) binary phase diagrams using the CALPHAD methodology from pre-fitted .tdb thermodynamic databases. This enables the prediction of solidus/liquidus lines, miscibility gaps, and invariant reactions (e.g. eutectics).
Instructions
1. Identify Thermodynamic Database
You must obtain a legitimate .tdb (Thermodynamic Data Base) file for the chemical system of interest.
- You can find databases in published literature or open repositories (like PyCalphad's databases).
2. Plot the Phase Diagram
Use the provided python script to generate the $T-x$ boundary plot.
# Env: calphad-agent
python .agents/skills/mat-calphad-phase-diagram/scripts/plot_phase_diagram.py path/to/database.tdb --elements Element1 Element2 --t-range 300 1000 10 --output research_dir/phase_diagram.png
--elements: The two chemical symbols to plot. The script computes the binary system.--t-range:START STOP STEPin Kelvin. It is recommended to use a step of 10 for reasonable trade-offs between calculation speed and curve smoothness.
3. Verification
Use a visual inspection tool to verify the resulting phase_diagram.png. Ensure that phase labels are clearly visible and there are no overlapping disjoint calculation artifacts (indicative of a database convergence issue).
Examples
Plotting the classic Aluminum-Zinc Phase Diagram (Mey 1993):
# Env: calphad-agent
python .agents/skills/mat-calphad-phase-diagram/scripts/plot_phase_diagram.py .agents/skills/mat-calphad-phase-diagram/examples/Al-Zn/alzn_mey.tdb --elements Al Zn --t-range 300 1000 10 --output Al-Zn_diagram.png
Constraints
- Databases: This skill strictly requires a valid
.tdbfile. - Environments: Scripts require the
calphad-agentConda environment because it isolatespycalphad. - Multicomponent: This specific plotting script focuses on Binary Systems. Ternary isotherms require a separate script not yet implemented.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 53 lines · 33 tokens per session scan A d32955c8c4ae
mat-calphad-phase-diagram is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (161 stars, last pushed 4d ago), licensed MIT. It adds 33 tokens to every session and 665 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
cd-calculator
Python calculators for geometry analysis, structural checking, solar calculations, panel optimization, mesh analysis, material estimation, and fabrication cost estimation for AEC computational design.
cd-calculator
Python calculators for geometry analysis, structural checking, solar calculations, panel optimization, mesh analysis, material estimation, and fabrication cost estimation for AEC computational design.
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.