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 Zhang-Henry/CoEvoSkills --skill evo-dicke-wignergit clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkillsWrote 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/zhang-henry/coevoskills/evo-dicke-wigner)<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/evo-dicke-wigner"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-dicke-wigner/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/zhang-henry/coevoskills/evo-dicke-wigner"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-dicke-wigner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00056 | $0.00509 |
| Opus 5 | $0.00028 | $0.00254 |
| Sonnet 5 | $0.00011 | $0.00102 |
| Haiku 4.5 | $0.00006 | $0.00051 |
Grade A, and why
evo-dicke-wigner 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.
What it actually says
Open Dicke Model Wigner Function Skill
This skill computes the steady-state Wigner function of the cavity field in an open Dicke model using QuTiP's PIQS module for collective spin operators.
Key Conventions
- Uses PIQS
Jxoperator (notJ+ + J-) with couplingg * (a + a†) ⊗ Jx - Builds spin Liouvillian with PIQS
Dickeclass including spin Hamiltonian - Combines cavity and spin Liouvillians with
super_tensor - Adds interaction via
spre/spostcommutator - Cavity is subsystem 0 for partial trace
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-dicke-wigner/scripts')
from utils import run_all_cases, validate_outputs
# Run all 4 cases and save CSVs
run_all_cases(output_dir='/root')
# Validate outputs
validate_outputs(output_dir='/root')
Functions
build_spin_hamiltonian(N, omega0)- Build ω₀Jz in Dicke basisbuild_spin_liouvillian(N, omega0, ...)- Build spin Liouvillian with PIQS Dickebuild_cavity_liouvillian(omega_c, n_max, kappa)- Build cavity Liouvillian with lossbuild_interaction_superop(N, n_max, g)- Build interaction superoperatorbuild_full_liouvillian(...)- Combine all parts into full Liouvillianfind_steady_state(L)- Find steady state density matrixget_cavity_state(rho_ss, n_max, nds)- Trace out spinscompute_wigner(rho_cav, xvec, yvec)- Compute Wigner functionsave_wigner_csv(W, filepath)- Save as CSVrun_case(...)- Run single case end-to-endrun_all_cases(output_dir)- Run all 4 casesvalidate_outputs(output_dir)- Validate all outputs
What ships with it
2 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.
- 12d ago First seen · 47 lines · 56 tokens per session scan A 20e6124e664b
evo-dicke-wigner is a skill published in the GitHub repository Zhang-Henry/CoEvoSkills (66 stars, last pushed 22d ago), licensed Apache-2.0. It adds 56 tokens to every session and 509 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.
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