hpc-quantum-espresso

hpc-quantum-espresso is a skill for Codex from SciMate-AI/HPC-Skills. It costs 67 tokens per session (521 once invoked), scanned A, original, MIT.

A guide for building and running Quantum ESPRESSO calculations, a physics program that predicts material properties from atoms. It covers input files, pseudopotentials, k-points, calculation stages, and convergence.

In plain words
What is it for?
Use it to create, review, debug, automate, restart, and post-process self-consistent-field, relaxation, band-structure, density-of-states, and related Quantum ESPRESSO workflows.
Why use it?
It helps avoid incorrect settings and difficult-to-diagnose failures when preparing calculations or running them on a computing cluster.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to create, review, debug, automate, restart, and post-process self-consistent-field, relaxation, band-structure, density-of-states, and related Quantum ESPRESSO workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/scimate-ai/hpc-skills/hpc-quantum-espresso
Install

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.

Any agent
npx skills add SciMate-AI/HPC-Skills --skill hpc-quantum-espresso
Clone the repo
git clone --depth 1 https://github.com/SciMate-AI/HPC-Skills

Made for: Codex.

Wrote 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.

agentmods badge for hpc-quantum-espresso

README.md
[![agentmods](https://agentmods.dev/badge/skills/scimate-ai/hpc-skills/hpc-quantum-espresso/github.svg)](https://agentmods.dev/skills/scimate-ai/hpc-skills/hpc-quantum-espresso)
Your own site
<a href="https://agentmods.dev/skills/scimate-ai/hpc-skills/hpc-quantum-espresso"><img src="https://agentmods.dev/badge/skills/scimate-ai/hpc-skills/hpc-quantum-espresso/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.

agentmods 80×15 button for hpc-quantum-espresso

Your own site · 80×15
<a href="https://agentmods.dev/skills/scimate-ai/hpc-skills/hpc-quantum-espresso"><img src="https://agentmods.dev/badge/skills/scimate-ai/hpc-skills/hpc-quantum-espresso.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 521 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.00521
Opus 5 $0.00034 $0.00260
Sonnet 5 $0.00013 $0.00104
Haiku 4.5 $0.00007 $0.00052

Measured 11d ago against content hash 06a0d21df91d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

hpc-quantum-espresso 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 11d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (assets/templates/qe-pwx-slurm.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/hpc-quantum-espresso/SKILL.md · 51 lines

What it actually says

HPC Quantum ESPRESSO

Treat Quantum ESPRESSO as a staged first-principles workflow centered on namelist-based input files.

Start

  1. Read references/pwx-workflow.md before creating or editing a pw.x input.
  2. Read references/input-and-parameter-matrix.md when mapping namelists, atomic species, pseudopotentials, and k-points.
  3. Read references/scf-relax-bands-and-convergence.md when choosing workflow stage and convergence strategy.
  4. Read references/cluster-execution-playbook.md when staging a Quantum ESPRESSO workflow for scheduler-backed cluster execution.
  5. Read references/error-recovery.md when SCF, relaxation, or input parsing fails.

Additional References

Load these on demand:

  • references/pseudopotential-kpoints-and-occupations.md for pseudo selection, k-point modes, and metallic versus insulating occupation logic
  • references/restarts-and-postprocessing.md for clean restarts, prefix/outdir, NSCF, DOS, and bands handoff
  • references/cutoff-and-mixing-matrix.md for ecutwfc, ecutrho, mixing, and SCF stabilization choices
  • references/cluster-execution-playbook.md for stage handoff, prefix or outdir discipline, and cluster launch choices

Reusable Templates

Use assets/templates/ when a concrete starting input is needed, especially:

  • scf_si.in
  • relax_si.in
  • bands_si.in
  • qe-pwx-slurm.sh

Guardrails

  • Do not mix pseudopotentials, cutoffs, and occupations without checking compatibility.
  • Do not treat k-point density as an afterthought.
  • Do not use a relaxation or bands workflow when the structure and SCF ground state are not ready.
  • Do not guess namelist keys from other DFT codes.

Outputs

Summarize:

  • workflow stage such as SCF, relax, or bands
  • pseudopotential and species setup
  • k-point strategy
  • key convergence controls and expected outputs
Changes

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.

  1. 11d ago First seen · 51 lines · 67 tokens per session scan A 06a0d21df91d

Subscribe to this mod's changes

hpc-quantum-espresso is a skill published in the GitHub repository SciMate-AI/HPC-Skills (86 stars, last pushed 5mo ago), licensed MIT. It adds 67 tokens to every session and 521 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

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…

anthropics/knowledge-work-plugins · 123 tokens

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…

K-Dense-AI/scientific-agent-skills · 83 tokens

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.

K-Dense-AI/scientific-agent-skills · 42 tokens

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.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens