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 agentmods add skills/learningmatter-mit/atomisticskills/mat-phase-diagramnpx skills add learningmatter-mit/AtomisticSkills --skill mat-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-phase-diagram)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/mat-phase-diagram"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/mat-phase-diagram.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00022 | $0.01115 |
| Opus 5 | $0.00011 | $0.00558 |
| Sonnet 5 | $0.00004 | $0.00223 |
| Haiku 4.5 | $0.00002 | $0.00112 |
Grade A, and why
mat-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 yesterday.
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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phase Diagram Retrieval
Goal
Retrieve pre-computed phase diagrams from Materials Project to analyze thermodynamic stability, competing phases, and convex hull relationships. Phase diagrams are essential for understanding:
- Which compounds are stable at 0 K
- Energy above hull (formation energy distance to the convex hull)
- Competing phases that may form during synthesis
- Thermodynamic driving forces for phase transformations
Instructions
1. Basic Phase Diagram Retrieval
Retrieve a phase diagram for a chemical system:
# Env: base-agent
python .agents/skills/mat-phase-diagram/scripts/get_phase_diagram.py \
--chemsys "Li-O" \
--output li_o_phase_diagram.json
Output: JSON file containing the phase diagram data (entries, energies, hull)
2. Generate Phase Diagram Plot
Add --plot flag to create a visualization:
# Env: base-agent
python .agents/skills/mat-phase-diagram/scripts/get_phase_diagram.py \
--chemsys "Li-O" \
--output li_o_pd.json \
--plot li_o_pd.png
Output: PNG plot showing the convex hull and stable/unstable phases
3. Use Different DFT Functional
By default, retrieves GGA+U phase diagrams. For R2SCAN data:
# Env: base-agent
python .agents/skills/mat-phase-diagram/scripts/get_phase_diagram.py \
--chemsys "Li-Fe-P-O" \
--thermo_type "R2SCAN" \
--output lifepo4_r2scan_pd.json \
--plot lifepo4_r2scan_pd.png
Thermo types:
GGA_GGA+U(default): Standard PBE with U correctionsR2SCAN: Meta-GGA functional (more accurate)GGA: Pure PBE without U corrections
Integration with Other Skills
With material-stability Skill
Use phase diagrams to visualize competing phases:
# 1. Get phase diagram
python .agents/skills/mat-phase-diagram/scripts/get_phase_diagram.py \
--chemsys "Li-O" \
--output li_o_pd.json \
--plot li_o_pd.png
# 2. Check specific material's position on hull
python .agents/skills/mat-db-mp/scripts/query_mp.py \
--formula "Li2O" \
--properties energy_above_hull formation_energy_per_atom \
--output li2o_stability.json
What ships with it
6 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.
- yesterday First seen · 140 lines · 22 tokens per session scan A eff87f3af766
mat-phase-diagram is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (160 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 1,115 once invoked, about $0.0001 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 2026-09-03.
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