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Protein Key Fragment Analysis
作者
wuhen9nine
· GitHub ↗
· v1.0.5
· MIT-0
389
总下载
0
收藏
0
当前安装
6
版本数
在 OpenClaw 中安装
/install protein-key-fragment-analysis
功能描述
蛋白质关键序列片段预测分析。对任意蛋白质家族的多物种FASTA序列执行完整分析流程,提取共识序列并识别关键功能片段、统计氨基酸组成、预测片段主要功能。适用于:(1)用户提到"提取蛋白关键序列/片段"、"分析蛋白保守区"、"预测蛋白功能片段"时,(2)对新物种/类群运行完整分析流程,(3)从已有FASTA序列提取共...
安全使用建议
What to check before installing or running this skill:
1) Code–doc mismatch: the docs and references repeatedly state that A/G/P (and X) are excluded from the amino-acid composition statistics, but the included script classifies A/G/P as Hydrophobic. This will materially change reported category counts, dominant-category calls, and downstream function predictions. Do not trust results until you verify/correct AA_CATEGORIES in scripts/protein_key_fragment_analysis.py and re-run a test.
2) Inspect for embedded data: the static scan found a 'base64-block' signature. Search all files for long base64-like blocks (e.g., lots of A–Z/a–z/0–9/+/=) and review their purpose. If you find any, open them and confirm they are just static example data or benign resources.
3) Run on non-sensitive data first: execute the scripts on small, public example FASTA files to confirm behavior, outputs, and runtime calls (the code calls clustalo via subprocess). Confirm no unexpected network activity (run in an isolated environment or monitor outbound connections during a test run).
4) Verify dependencies and runtime: ClustalOmega is required and invoked via subprocess. Ensure you have the correct version installed and that the environment where you run the skill is trusted.
5) Review other truncated files: the package contains many precomputed results; scan any remaining/truncated files for hidden scripts, obfuscated content, or instructions that differ from SKILL.md. Because parts of the code were truncated in the review, further review could reveal additional inconsistencies.
6) If you plan to use this for research or decision-making, validate predictions experimentally or via established annotation tools (Pfam/InterPro/AlphaFold) — the tool itself documents limitations and is heuristic.
If you want, I can: (a) point to the exact lines in the script to change to make A/G/P excluded, (b) produce a small checklist of commands to run the package safely in an isolated environment, or (c) search the full file list for base64-like blocks and show their locations.
功能分析
Type: OpenClaw Skill
Name: protein-key-fragment-analysis
Version: 1.0.5
The skill bundle is a legitimate bioinformatics tool designed for protein sequence analysis, including Multiple Sequence Alignment (MSA) using ClustalOmega, consensus sequence extraction, and functional fragment prediction. The Python scripts (protein_key_fragment_analysis.py and run_full_analysis.py) perform standard file operations and execute the 'clustalo' system command using safe subprocess calls without shell execution. There is no evidence of data exfiltration, malicious persistence, or prompt injection attempts; the behavior is entirely consistent with the stated purpose.
能力评估
Purpose & Capability
Name/description (consensus/MSA → fragment extraction → composition → function prediction) matches the provided scripts and example outputs. The code implements MSA invocation (via ClustalOmega) and generates the reported JSON/MD outputs, so purpose and capability are largely aligned.
Instruction Scope
SKILL.md and references describe excluding A/G/P/X from composition statistics, but the shipped script's AA_CATEGORIES explicitly includes A/G/P inside the Hydrophobic class (implementation contradicts docs). That affects outputs and downstream function_prediciton logic. SKILL.md also recommends installing ClustalOmega and editing script constants (KNOWN_MOTIFS/CONSERVED_BLOCKS) — editing code is expected for custom families but increases risk of accidental misconfiguration. A pre-scan detected a 'base64-block' pattern in SKILL.md content (or other files), which could indicate embedded data or an attempt at prompt-injection; this should be inspected.
Install Mechanism
No install spec; instruction-only install steps ask users to install ClustalOmega via apt/conda. Using a local well-known bioinformatics binary is proportionate. There are no remote download/install steps in metadata.
Credentials
The skill requires no environment variables, credentials, or special config paths. It reads local FASTA inputs and writes local reports — credential requests are proportionate (none requested).
Persistence & Privilege
Skill is not always-enabled, does not request persistent system-wide privileges, and contains only scripts and static references. Autonomous invocation is allowed by platform default but not combined with other privilege escalations here.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install protein-key-fragment-analysis - 安装完成后,直接呼叫该 Skill 的名称或使用
/protein-key-fragment-analysis触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.5
修正依赖声明:明确Python版本要求和系统依赖(clustalo)
v1.0.4
更新SKILL.md:完善关键片段识别流程、氨基酸组成分析、功能预测规则的详细描述
v1.0.3
移除特定蛋白家族案例,改为通用化表述;强调适用于任何蛋白质家族;功能预测标签去除家族特异性描述
v1.0.2
修正氨基酸分类:A/G/P 排除不统计(原错误归入Hydrophobic);新增Step5功能预测(12条优先级规则);更新method.md补充组成分析和功能预测方法细节;分类体系与aa-pair-analysis完全统一
v1.0.1
Update: Fixed acceptLicenseTerms issue
v1.0.0
Initial release: MSA to consensus to key fragment prediction for any protein family
元数据
常见问题
Protein Key Fragment Analysis 是什么?
蛋白质关键序列片段预测分析。对任意蛋白质家族的多物种FASTA序列执行完整分析流程,提取共识序列并识别关键功能片段、统计氨基酸组成、预测片段主要功能。适用于:(1)用户提到"提取蛋白关键序列/片段"、"分析蛋白保守区"、"预测蛋白功能片段"时,(2)对新物种/类群运行完整分析流程,(3)从已有FASTA序列提取共... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 389 次。
如何安装 Protein Key Fragment Analysis?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install protein-key-fragment-analysis」即可一键安装,无需额外配置。
Protein Key Fragment Analysis 是免费的吗?
是的,Protein Key Fragment Analysis 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Protein Key Fragment Analysis 支持哪些平台?
Protein Key Fragment Analysis 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Protein Key Fragment Analysis?
由 wuhen9nine(@wuhen9nine)开发并维护,当前版本 v1.0.5。
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