SKILLEMALL.ai

AC gromacs-skills

GROMACS 分子动力学模拟软件命令参考。当 Agent 需要执行 GROMACS 命令但不清楚用法时调用。功能覆盖:(1) 拓扑与结构处理 - pdb2gmx、editconf、solvate、insert-molecules、genrestr;(2) 模拟设置与运行 - grompp、mdrun;(3) 轨迹处理 - trjconv(PBC修正、格式转换)、trjcat(轨迹拼接);(4) 能量分析 - energy、eneconv、bar;(5) 轨迹分析 - rms、rmsf、gyrate、hbond、distance、angle、dihedral、sasa、cluster、mindist;(6) 结构分析 - covar、anaeig(PCA)、mdmat、sham(FEL);(7) 索引与选择 - make_ndx、select、genion;(8) 工具 - xpm2ps、check、wham。强调优先使用 gmx <command> -h 查看本地帮助。

ClawHub Agent Skills author: CharlesHahn v1.0.0 MIT-0 4 files body ≈ 1 179 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 55/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 27 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1179 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low 13 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 442: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 27 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This is a Markdown-only GROMACS command reference with disclosed local command examples that fit molecular simulation work.
LLM: benign (high) · VirusTotal: · 29 May 2026