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 beita6969/ScienceClaw --skill materials-sciencegit clone --depth 1 https://github.com/beita6969/ScienceClawWrote 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/beita6969/scienceclaw/materials-science)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/materials-science"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/materials-science/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/materials-science"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/materials-science.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00049 | $0.00712 |
| Opus 5 | $0.00024 | $0.00356 |
| Sonnet 5 | $0.00010 | $0.00142 |
| Haiku 4.5 | $0.00005 | $0.00071 |
Grade A, and why
materials-science 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 9d 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.
When to Trigger
Activate this skill when the user mentions:
- Crystal structures, lattice parameters, space groups, unit cells
- Phase diagrams, phase transitions, thermodynamic stability
- Mechanical properties (tensile strength, hardness, elastic modulus)
- Electronic properties (band gap, conductivity, dielectric constant)
- Materials characterization (XRD, SEM, TEM, AFM)
- Nanomaterials, thin films, composites, polymers
- Materials databases, high-throughput screening, materials informatics
Step-by-Step Methodology
- Define the materials question - Specify the material system (elements, compounds), property of interest, and application context (structural, electronic, optical, catalytic).
- Database search - Query Materials Project, AFLOW, ICSD, or OQMD for known structures and computed properties. Check experimental databases (Springer Materials, NIST) for measured values.
- Structure analysis - Identify crystal system, space group, and Wyckoff positions. Compute lattice parameters and density. For disordered systems, characterize using pair distribution functions or radial distribution functions.
- Property evaluation - Retrieve or compute relevant properties: formation energy (thermodynamic stability), band structure (electronic), phonon dispersion (thermal), elastic tensor (mechanical). Compare with target specifications.
- Phase diagram analysis - Construct or retrieve phase diagrams (binary, ternary). Identify stable phases, invariant reactions (eutectic, peritectic), and solid solutions. Use CALPHAD method for complex systems.
- Characterization guidance - Recommend appropriate techniques: XRD for crystal structure, SEM/TEM for microstructure, XPS for surface chemistry, DSC for thermal transitions. Specify expected peaks/features.
- Design recommendations - Suggest composition or processing modifications to achieve target properties. Consider trade-offs between competing properties (strength vs. ductility, conductivity vs. transparency).
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.
- 9d ago First seen · 53 lines · 49 tokens per session scan A fd911a86045a
materials-science is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 49 tokens to every session and 712 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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