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 SFETNI/Deep-Matter-Chem-Skills --skill crystal-plasticity-workflowgit clone --depth 1 https://github.com/SFETNI/Deep-Matter-Chem-SkillsWrote 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/sfetni/deep-matter-chem-skills/crystal-plasticity-workflow)<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/crystal-plasticity-workflow"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/crystal-plasticity-workflow/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/sfetni/deep-matter-chem-skills/crystal-plasticity-workflow"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/crystal-plasticity-workflow.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00007 | $0.06883 |
| Opus 5 | $0.00003 | $0.03442 |
| Sonnet 5 | $0.00001 | $0.01377 |
| Haiku 4.5 | $0.00001 | $0.00688 |
Grade A, and why
crystal-plasticity-workflow 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 12d 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 — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Crystal Plasticity Workflow
Description
This skill covers crystal plasticity and crystal plasticity finite element (CPFE) modeling of metals: orientation representations and conventions, slip-system definitions for FCC/BCC/HCP, resolved shear stress and Schmid factors, the multiplicative decomposition F = Fe Fp, rate-dependent and rate-independent flow rules, hardening laws, single-crystal and polycrystal (RVE) simulation, texture evolution, parameter calibration and identifiability, and validation against stress-strain curves and crystallographic observables. Invoke this skill when anisotropy, crystallographic slip, texture evolution, or grain-scale heterogeneity control the mechanical response and an isotropic or phenomenological anisotropic plasticity model is insufficient.
Domain Context
Crystal plasticity resolves plastic deformation onto crystallographic slip systems rather than treating the material as an isotropic continuum. It sits above dislocation dynamics and below macroscopic phenomenological plasticity: it does not resolve individual dislocations, but it carries crystallographic orientation, slip-system geometry, and their evolution, which lets it predict anisotropy, lattice rotation, and texture development that isotropic J2 plasticity cannot. Choosing the right model tier matters — isotropic plasticity for texture-free bulk response, phenomenological anisotropic (e.g. Hill/Barlat) yield surfaces for formability without explicit crystallography, crystal plasticity when slip-system activity and orientation evolution are the target, and CPFE when grain morphology and intergranular stress fields must be spatially resolved.
The kinematic core is the multiplicative decomposition of the deformation gradient F = Fe Fp, where Fp accumulates plastic shear on slip systems and Fe carries elastic stretch and lattice rotation. The plastic velocity gradient Lp = Fp_dot Fp^{-1} is a sum over slip systems of shear rate times the Schmid tensor (slip direction dyad slip-plane normal). The resolved shear stress on each system is the projection of the Mandel/second Piola-Kirchhoff stress onto its Schmid tensor, and slip is driven by that resolved stress relative to a slip resistance. Rate-dependent (viscoplastic power-law) formulations regularize slip-system selection and improve convergence at the cost of a rate-sensitivity parameter; rate-independent formulations require an active-set or singular-value treatment of the ambiguous slip-selection problem. [EXPERT REVIEW NEEDED]
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.
- 12d ago First seen · 375 lines · 7 tokens per session scan A a89dea08394d
crystal-plasticity-workflow is a skill published in the GitHub repository SFETNI/Deep-Matter-Chem-Skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 7 tokens to every session and 6,883 once invoked, about $0.0000 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 2026-08-31.
Other skills, from other repositories
datamol
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters…
smiles-validation
Strict SMILES validation, structural comparison, and modification verification. Catches invalid LLM-generated molecules.
patsnap-biological-modality
Biological sequence and modality intelligence via Patsnap MCP.
patsnap-scientific-translational-evidence
Patsnap Scientific & Translational Evidence MCP for AI agents. Retrieval platform focusing on scientific literature and translational outcomes, covering academic publication queries and translational medicine record tracking.
patsnap-target-disease
Patsnap Target & Disease MCP for AI agents. Target and disease profiling tool, covering target characterization, disease profiling, and epidemiology evidence retrieval.
patsnap-solution-engine
Patsnap TRIZ Concept Solution Engine MCP for AI agents. Generates innovation or product cost-reduction concepts through asynchronous TRIZ and TRIZ/DFMA workflows. Use for engineering problem solving, concept alternatives, cost-reduction analysis, task-progress retrieval, and selected-solution details.