onescience-data-analyzer

A data-analysis skill for OneScience, a research-focused AI platform. It accepts task details from the conversation or from handoff files, then carries out analysis, charts, and report generation.

In plain words
What is it for?
Use it for statistical and trend analysis, correlation analysis, scientific visualisations, interactive charts, and structured reports with exported results.
Why use it?
It separates planning from execution and provides a defined way to pass tasks and results between workflow steps. It can also match visualisation work to scientific fields such as biology or meteorology.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/onescience-ai/oneskills/onescience-data-analyzer
Any agent
npx skills add onescience-ai/OneSkills --skill onescience-data-analyzer
Clone the repo
git clone --depth 1 https://github.com/onescience-ai/OneSkills

Made for: Claude Code, Codex.

Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,271 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00073 $0.03271
Opus 5 $0.00036 $0.01636
Sonnet 5 $0.00015 $0.00654
Haiku 4.5 $0.00007 $0.00327

Measured 2d ago against content hash 3760af635ced, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

onescience-data-analyzer 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 2d 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.

skills/onescience-data-analyzer/SKILL.md · 198 lines

How it starts

The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.

输入获取方式

本技能支持两种输入方式:

  1. 上下文 handoff(默认):从调用方传入的 step_handoff 获取任务信息。
  2. 文件 handoff(autonomous_mode):从 .onescience/handoff/step_{step_id}.yaml 读取任务信息。执行后,将结果写入 .onescience/handoff/step_{step_id}_result.yaml

启动时优先检查 .onescience/handoff/ 目录是否存在对应的交接文件;若存在则使用文件模式,否则使用上下文模式。

文件交接格式参见 skills/onescience-orchestrator/references/file_handoff_contract.md

onescience-data-analyzer

数据分析执行技能,负责数据分析、可视化与报告输出。

职责

本技能为执行器(executor),专注于执行数据分析任务,不涉及任务规划。规划由其他技能完成后传递给本技能执行。

核心能力

  1. 数据分析:统计分析、趋势分析、相关性分析
  2. 数据可视化:图表生成、多维展示、交互式可视化
  3. 报告生成:结构化报告、图文结合、结果导出

工作流调用

根据任务类型调用对应工作流:

  • 统计分析{{workflow:references/statistical_analysis.md}}
  • 可视化生成{{workflow:references/visualization.md}}
  • 报告输出{{workflow:references/report_generation.md}}

领域知识

工作流执行时会根据数据领域自动匹配 assets/ 目录中的领域知识:

  • 气象数据可视化:assets/meteorology_viz.md
  • 生物信息学可视化:assets/bioinformatics_viz.md
  • 流体力学可视化:assets/fluid_dynamics_viz.md
  • 材料科学可视化:assets/materials_science_viz.md

结构可视化原语

先将 biobiologybioinformatics 归一化为生信领域。当输入为 .pdb.cif.mmcif,或 requirements.viz_type=complex_structure 时:

阶段一:执行资产获取

  1. step_handoff.resource_bindings 已包含 visualization_primitive 的完整 contentcontent.execution_assets

    • 先检查 execution_assets_summary:若 unavailable + failed == total,跳过校验直接进入阶段二降级决策。
    • 否则遍历每个资产,校验 statusavailablematerialized 的资产 SHA-256,再物化到工作区。
  2. 若资源绑定不完整或缺少执行资产,按以下优先级获取:

    a. 【优先】直接使用 catalog_search:调用 catalog_search 工具(kind=primitive, domain=bio, q=complex_structure_visualization)。此路径直接查询 OneCode 内置 catalog(含 bundled seed 原语),不依赖 onescience-primitives 技能的间接协议,避免因消息模拟链路中的工具可用性或参数传递问题导致检索失败。若命中:

    • 使用 catalog_resolve(id, part=body) 获取完整内容(含 execution_assets
    • 提取 matched_resourcestype=visualization_primitive 的资源
    • 直接跳转到阶段一的步骤 3(召回结果校验),跳过步骤 2b

    b. 【回退】通过 onescience-primitives 协议获取:仅当 catalog_search 未命中时,向 onescience-primitives 发起以下资源召回请求:

    • user_request:必须包含可视化信号词(如"交互式 3D 蛋白质结构可视化、pLDDT 置信度着色、PAE 热图渲染"),确保 primitives 技能能正确路由到 visualization category
    • content_request: "完整内容"
    • include_execution_assets: true
    • filters.domain: bio
    • filters.keyword: complex_structure_visualization必须使用下划线分隔的精确目录名,以触发 primitives 的命名直查模式,绕过语义排序和截断)
    • 不得沿返回的裸 path 直接读取原语资产
  3. 【强制】召回结果校验:根据检索路径不同,校验方式如下:

Read the full file on GitHub · 198 lines

Files

What ships with it

7 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.

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. 2d ago First seen · 198 lines · 73 tokens per session scan A 3760af635ced

Subscribe to this mod's changes

onescience-data-analyzer is a skill published in the GitHub repository onescience-ai/OneSkills (18 stars, last pushed 19d ago), licensed MIT. It adds 73 tokens to every session and 3,271 once invoked, about $0.0004 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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