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BF aa-pair-analysis

蛋白质氨基酸功能类别相邻对频率分析。对任意蛋白质家族的多物种序列进行多序列比对（MSA）、共识序列提取、对型统计和配方计算，输出Top5高频对型及φ值。适用于：（1）对新物种/类群运行完整分析流程，（2）从已有共识序列进行对型统计，（3）横向比较不同物种/类群的氨基酸对组成差异，（4）修改氨基酸分类或统计参数后重新分析。适用于任何蛋白质家族。

ClawHub Agent Skills author: wuhen9nine v1.1.0 MIT-0 12 files · 1 script body ≈ 728 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 35/100 · Will not run — References files that are not bundled: scripts/run_combined_analysis.py

AnalyzerSoftware developmentData and analyticsPeople and hiringtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
95
Quality 40%
67
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: scripts/run_combined_analysis.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Dangerous commands cmd-shell-rc scripts/setup.sh:111
    Writes to a shell startup file
    echo "export PATH=\"\$HOME/.local/bin:\$PATH\"" >> "$HOME/.bashrc"

Files scanned: 12. 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")
  • warning missing-ref reference to a missing file: scripts/run_combined_analysis.py

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: scripts/run_combined_analysis.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/run_combined_analysis.py
  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 100Steps. 25 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 728 tokens
  • 100Running it twice. No mutating operations

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
  • -31 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 172: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
The skill’s protein-analysis purpose is coherent, but its installer can install an unverified executable over plain HTTP and make persistent shell changes.
LLM: suspicious (high) · VirusTotal: · 29 May 2026