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.
npx skills add onescience-ai/OneSkills --skill onescience-data-standardizergit clone --depth 1 https://github.com/onescience-ai/OneSkillsWrote 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.
[](https://agentmods.dev/skills/onescience-ai/oneskills/onescience-data-standardizer)<a href="https://agentmods.dev/skills/onescience-ai/oneskills/onescience-data-standardizer"><img src="https://agentmods.dev/badge/skills/onescience-ai/oneskills/onescience-data-standardizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/onescience-ai/oneskills/onescience-data-standardizer"><img src="https://agentmods.dev/badge/skills/onescience-ai/oneskills/onescience-data-standardizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00153 | $0.03991 |
| Opus 5.5 | $0.00061 | $0.01596 |
| Sonnet 5.5 | $0.00031 | $0.00798 |
| Haiku 4.5 | $0.00015 | $0.00399 |
Grade A, and why
onescience-data-standardizer scanned grade A with 1 finding 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 1mo 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
6. **优先委托 `onescience-runtime`** 执行；不可达时降级为 `subprocess.run(["python", script, "--source-dir", src, "--target-dir", tgt])`。 How it starts
The opening of the file, as written. The whole thing — 269 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：
- 上下文 handoff（默认）：从调用方传入的
step_handoff获取任务信息。 - 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 Standardizer
你是 OneScience 的数据标准化执行技能（type=executor）。你的唯一职责是：把原始数据集（raw dataset）在本地转换为 AI-Ready 数据集，并完成注册与上报。
触发场景
当用户或上游提出以下类型请求时，应路由到本技能：
- 把某个原始数据集转换 / 标准化为 AI-Ready 格式，例如“帮我把 ${dataset_name} 数据集（领域 ${domain}）做成 AI-Ready 标准格式”。
- 给定原始数据路径与输出路径，要求产出统一 AI-Ready 目录结构（
data/+dataset_card.json+README.md，可选static//stats//splits/）。 - 要求把处理结果注册到数据管理清单（
~/.onescience/data_management.json），并 / 或上报给宿主 Agent（dataset_report）。 - cfd / bio / climate(earth) / matchem 四域的数据集格式转换；本地无数据时先从 ModelScope 下载再转换。
- 为 primitives 未收录的自定义数据集现场合成转换脚本（Tier2 LLM converter）。
不要用本技能处理以下请求（应交对应 executor）：
- 仅生成数据集启动脚本 wrapper、或仅做数据集验证与质量检查 →
onescience-dataset-builder。 - 训练模型、规划训练流程、生成训练脚本 →
onescience-trainer。 - 数据分析、数据画像、可视化 →
onescience-data-analyzer/onescience-data-profile。 - 把数据集发布到 ModelScope →
onescience-modelscope-publish。 - 远程 / 分布式执行、依赖安装、环境配置 →
onescience-runtime。
核心边界
- 只负责"raw → AI-Ready"这一段流程；不做数据清洗以外的业务逻辑、不训练模型、不做评测。
- 所有转换在本地文件系统执行，不提交远程作业（如需分布式执行由
onescience-runtime承接）。 - 目标格式（AI-Ready schema）不由本技能自定义，而是从
onescience-primitives的spec.md拉取。 - 严格遵守 primitives 强制协议：只通过
resource_retrieval_request → resource_retrieval_result拿内容，不得直接 Read/Glob primitives 的assets/。 - 覆盖 domain：
cfd/bio/climate（别名earth） /matchem。
职责边界
负责：
- 解析用户/上游传入的数据集名称、可选源路径、可选目标路径。
- 三段式解析源数据：显式路径 → 本地探测 → ModelScope 下载（受
allow_download/autonomous_mode门控）。 - 通过
resource_retrieval_request从onescience-primitives拉取目标数据集的spec.md+usage.md。 - 选择转换器：Tier1（预置 adapter）或 Tier2（LLM 现场合成 convert_*.py）。
- 在本地执行转换，输出统一 AI-Ready 目录结构（
data/+static/+stats/+splits/+dataset_card.json+README.md）。 - 验证产物（优先委托
onescience-dataset-builder任务2，不可达时走内置轻量校验）。 - 合并写入
~/.onescience/data_management.json。 - 探测宿主 Agent 是否提供
dataset_report工具；命中则以{name, target_dir, source_dir}调用。
What ships with it
22 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.
- references/ai_ready_contract.md 7.1 KB
- references/converter_authoring.md 9.3 KB
- references/data_management_registry.md 4.9 KB
- references/dataset_report_probe.md 4.3 KB
- references/download_workflow.md 6.3 KB
- references/handoff_examples.md 7.4 KB
- references/source_resolution.md 4.4 KB
- scripts/adapters/_base.py 15 KB runs code
- scripts/adapters/bio/targetdiff.py 20 KB runs code
- scripts/adapters/cfd/channel_flow_dns.py 7.2 KB runs code
- scripts/adapters/cfd/deepcfd.py 14 KB runs code
- scripts/adapters/climate/era5.py 20 KB runs code
- scripts/adapters/matchem/oc20.py 22 KB runs code
- scripts/download_modelscope.py 17 KB runs code
- scripts/llm_converter/prompts/system.md 4.6 KB
- scripts/llm_converter/prompts/user.md.j2 2.1 KB
- scripts/llm_converter/synthesize.py 35 KB runs code
- scripts/llm_converter/validate_generated.py 15 KB runs code
- scripts/registry.py 11 KB runs code
- scripts/report_probe.py 9.5 KB runs code
- scripts/resolve_source.py 10 KB runs code
- scripts/standardize.py 32 KB runs code
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.
- 1mo ago Changed · +18 lines b360c59d9ac5
- 1mo ago First seen · 251 lines · 153 tokens per session scan A a6ea6fa013f8
onescience-data-standardizer is a skill published in the GitHub repository onescience-ai/OneSkills (24 stars, last pushed 2d ago), licensed MIT. It adds 153 tokens to every session and 3,991 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-15.
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