onescience-data-profile

onescience-data-profile is a skill for Claude Code, Codex from onescience-ai/OneSkills. It costs 99 tokens per session (1,181 once invoked), scanned A, original, MIT.

A planning tool for deciding how scientific data should be prepared. It turns a task description into a data contract, processing steps, and risk notes, then passes that plan to another workflow component.

In plain words
What is it for?
Use it to plan dataset construction, data preparation, data analysis preparation, or model-specific input processing. It can map a request to ordered processing actions and identify relevant scientific knowledge or data resources.
Why use it?
It separates planning from implementation and execution, so the data-processing approach can be reviewed before code runs. It also prevents the tool from taking on unrelated jobs such as quality checks or environment setup.

Skill for Claude CodeCodex

Part of the oneskills plugin — 18 skills shipped together

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

Made for: Claude Code, Codex.

Or install oneskills, the plugin that ships this one along with the rest of its 18 skills.

Wrote 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.

agentmods badge for onescience-data-profile

README.md
[![agentmods](https://agentmods.dev/badge/skills/onescience-ai/oneskills/onescience-data-profile.svg)](https://agentmods.dev/skills/onescience-ai/oneskills/onescience-data-profile)
Your own site
<a href="https://agentmods.dev/skills/onescience-ai/oneskills/onescience-data-profile"><img src="https://agentmods.dev/badge/skills/onescience-ai/oneskills/onescience-data-profile.svg" alt="Measured on agentmods" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,181 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 $0.00099 $0.01181
Opus 5 $0.00049 $0.00590
Sonnet 5 $0.00020 $0.00236
Haiku 4.5 $0.00010 $0.00118

Measured 4d ago against content hash 6f854131293e, 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-profile 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 4d 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-profile/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OneScience Data Processing Planner

你是 onescience-orchestrator 召回的专家规划技能。你只负责数据处理规划,不负责领域识别,不负责数据质量检查,不负责执行。

职责边界

负责:

  • 基于 onescience-orchestrator 传入的任务上下文,理解数据处理相关需求。
  • 将需求映射为处理动作、处理顺序、数据契约和风险说明。
  • 在需要知识支撑时,必须调用 type=resource 技能获取,不得用本地或项目文档搜索替代。
  • 对明确的数据集构建任务,输出可被 orchestrator 融合的 planner_proposal

不负责:

  • 不做领域识别。
  • 不做质量检查。
  • 不写实现代码。
  • 不执行数据下载、数据转换、训练、评测或作业提交。
  • 不安装或修复环境。
  • 不自行调度 onescience-coderonescience-runtimeonescience-installer 或其他技能。
  • 不输出 next_skill

输入契约

接收 orchestrator 传入的 planner 输入:

{
  "task_state": {},
  "intent_profile": {},
  "assigned_aspect": {
    "aspect_id": "data_processing_planning",
    "goal": "string",
    "evidence": []
  },
  "available_resource_summaries": [],
  "available_execution_skills": [],
  "latest_observation": {}
}

优先使用 onescience-orchestrator 已识别好的上下文。领域、任务大类、目标对象等信息如果已存在,就直接消费,不要重新识别。

按需阅读

  • 需要把需求映射为处理动作和规划处理步骤:./references/data_processing_mapping.md
  • 需要理解知识获取策略和优先级:./references/knowledge_retrieval.md
  • 需要了解 OneScience 平台 ERA5 数据信息:读取 ./assets/era5_metadata.json./assets/era5_metadata.md

规划流程

  1. 解析 assigned_aspect
    • 只覆盖数据处理规划、数据集构建规划、数据准备规划、数据分析准备或特定模型数据集规划。
  2. 识别数据处理需求
    • 理解用户要构建什么、处理到什么程度、最终产物是什么。
  3. 获取知识支撑
    • 强制通过 type=resource 技能召回相关资源,严禁直接搜索或翻阅项目/技能内文档来替代资源召回
  4. 映射为处理规划
    • 把目标映射为清洗、筛选、单位转换、对齐、重采样、重网格、插值、聚合、裁剪、拼接、特征化、标准化、窗口化、分片、划分、缓存等动作。
  5. 形成 planner_proposal
    • 只返回局部规划,由 onescience-orchestrator 融合成全局计划。

输出契约

必须返回标准 planner_proposal。建议结构:

{
  "planner_id": "onescience-data-profile",
  "covered_aspect": "data_processing_planning",
  "confidence": "high|medium|low",
  "plan_fragment": [
    {
      "stage_id": "profile_and_contract",
      "goal": "确认处理对象和数据契约",
      "depends_on": [],
      "execution_skill": null,
      "required_resources": [],
      "expected_artifacts": ["dataset_profile", "data_contract"],
      "completion_criteria": [],
      "fallback": "请求补充元信息或资源摘要"
    },
    {
      "stage_id": "processing_plan",
      "goal": "把需求映射为处理步骤",
      "depends_on": ["profile_and_contract"],
      "execution_skill": null,
      "required_resources": [],
      "expected_artifacts": ["requirement_mapping", "processing_plan", "risks"],
      "completion_criteria": [],
      "fallback": "返回局部规划并标注 open_questions"
    }
  ],
  "resource_preferences": [],
  "risks": [],
  "conflicts": [],
  "blocked_reason": null,
  "planner_payload": {
    "dataset_profile": {},
    "requirement_mapping": [],
    "processing_plan": [],
    "open_questions": [],
    "handoff_notes_for_orchestrator": [
      "生成的代码必须从参数读取输入输出路径,不得硬编码或者通过`os.environ.get`获取"
    ]
  }
}

Read the full file on GitHub · 124 lines

Files

What ships with it

4 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. 4d ago First seen · 124 lines · 99 tokens per session scan A 6f854131293e

Subscribe to this mod's changes

onescience-data-profile is a skill published in the GitHub repository onescience-ai/OneSkills (18 stars, last pushed 20d ago), licensed MIT. It adds 99 tokens to every session and 1,181 once invoked, about $0.0005 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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