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-db-mpnpx skills add learningmatter-mit/AtomisticSkills --skill mat-db-mpgit 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-db-mp)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/mat-db-mp"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/mat-db-mp.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 | $0.00031 | $0.02714 |
| Opus 5 | $0.00015 | $0.01357 |
| Sonnet 5 | $0.00006 | $0.00543 |
| Haiku 4.5 | $0.00003 | $0.00271 |
Grade A, and why
mat-db-mp 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 today.
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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Materials Project Database Query
Goal
To retrieve crystal structures and computed properties from the Materials Project database, enabling efficient materials discovery and property analysis. This skill provides access to:
- Basic material properties (energy above hull, formation energy, band gap)
- Elastic properties (bulk modulus, shear modulus, elastic tensors)
- Magnetic properties (magnetic ordering, magnetization, site moments)
- Structure similarity search (CrystalNN-based fingerprinting)
Note: For quick structure retrieval by formula or chemical system, MCP tools are also available (see MCP Tools section).
Instructions
1. Query Materials by Chemical System or Formula
Use query_mp.py to search for materials by chemical system, formula, or elements with property filtering.
Basic Query (Summary Endpoint):
# Env: base-agent
python .agents/skills/mat-db-mp/scripts/query_mp.py \
--chemsys "Li-S" \
--properties energy_above_hull formation_energy_per_atom band_gap \
--e_above_hull_max 0.05 \
--limit 10 \
--endpoint summary \
--output stable_li_s_materials.json
Detailed Thermodynamic Data (Thermo Endpoint):
# Env: base-agent
python .agents/skills/mat-db-mp/scripts/query_mp.py \
--chemsys "Li-O" \
--endpoint thermo \
--limit 20 \
--output li_o_thermo.json
Key Parameters:
--chemsys: Chemical system (e.g., "Li-S", "Si-O")--formula: Specific chemical formula (e.g., "LiFePO4")--elements: List of elements that must be present--properties: Properties to retrieve (default: energy_above_hull, formation_energy_per_atom)--e_above_hull_max: Maximum energy above hull for stability filtering (eV/atom)--endpoint: Choosesummary(includes structures) orthermo(detailed thermodynamics, no structures)--limit: Maximum number of results to retrieve
Output: JSON file containing material IDs, formulas, CIF strings (summary endpoint), and requested properties.
What ships with it
22 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.
- examples/elasticity/elasticity_query.sh 782 B runs code
- examples/elasticity/high_bulk_modulus.json 85 KB
- examples/elasticity/si_elasticity.json 17 KB
- examples/get_structure/mp-1143.cif 1.4 KB
- examples/get_structure/mp-149_Si.cif 764 B
- examples/get_structure/mp-149.cif 764 B
- examples/get_structure/mp-19017.cif 2.5 KB
- examples/get_structure/structure_retrieval.sh 1015 B runs code
- examples/magnetism/fe2o3_magnetism.json 2.3 KB
- examples/magnetism/ferromagnetic_materials.json 8.9 KB
- examples/magnetism/magnetism_query.sh 832 B runs code
- examples/query_mp/li_s_stability.sh 719 B runs code
- examples/query_mp/li_s_stable.json 2.3 KB
- examples/README.md 3.8 KB
- examples/similarity/similar_si_carbon_only.json 40 B
- examples/similarity/similar_to_si.json 1.8 KB
- examples/similarity/similarity_search.sh 826 B runs code
- scripts/find_similar_structures.py 10 KB runs code
- scripts/get_elasticity.py 6.7 KB runs code
- scripts/get_magnetism.py 6.5 KB runs code
- scripts/get_structure_by_id.py 4.5 KB runs code
- scripts/query_mp.py 17 KB runs code
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.
- today First seen · 301 lines · 31 tokens per session scan A 38a7f7888890
mat-db-mp is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (158 stars, last pushed today), licensed MIT. It adds 31 tokens to every session and 2,714 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 2026-09-03.
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