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 OpenDCAI/DataFlow-WebUI --skill dataflow-operator-buildergit clone --depth 1 https://github.com/OpenDCAI/DataFlow-WebUIWrote 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/opendcai/dataflow-webui/dataflow-operator-builder)<a href="https://agentmods.dev/skills/opendcai/dataflow-webui/dataflow-operator-builder"><img src="https://agentmods.dev/badge/skills/opendcai/dataflow-webui/dataflow-operator-builder/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/opendcai/dataflow-webui/dataflow-operator-builder"><img src="https://agentmods.dev/badge/skills/opendcai/dataflow-webui/dataflow-operator-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 12 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00066 | $0.02078 |
| Opus 5.5 | $0.00026 | $0.00831 |
| Sonnet 5.5 | $0.00013 | $0.00416 |
| Haiku 4.5 | $0.00007 | $0.00208 |
Grade A, and why
dataflow-operator-builder 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DataFlow Operator Builder
Build production-ready DataFlow operator artifacts with either interactive interview mode or direct spec mode.
ZH: 通过“交互采访模式”或“直接 spec 模式”快速生成生产可用的 DataFlow Operator。
Usage
/dataflow-operator-builder
/dataflow-operator-builder --spec path/to/spec.json --output-root path/to/repo
/dataflow-operator-builder --dry-run --spec path/to/spec.json --output-root path/to/repo
Script Directory
Agent execution instructions:
- Resolve this
SKILL.mddirectory asSKILL_DIR. - Use
${SKILL_DIR}/scripts/build_operator_artifacts.py.
ZH:
- 将当前
SKILL.md所在目录作为SKILL_DIR。 - 使用
${SKILL_DIR}/scripts/build_operator_artifacts.py。
| Script | Purpose |
|---|---|
scripts/build_operator_artifacts.py |
Generate operator + CLI + tests from spec |
scripts/example_spec.json |
Example input spec with defaults |
Scope
This skill targets:
- DataFlow-style operator implementation (
DataFlowStorage+ dataframe flow) @OPERATOR_REGISTRY.register()registration- Separate CLI wrapper under
cli/ - Minimal but production-grade tests (
unit/registry/smoke)
ZH:
- 面向 DataFlow 风格的 operator 实现（
DataFlowStorage+ dataframe 流程） - 自动包含
@OPERATOR_REGISTRY.register()注册 - CLI 与 operator 逻辑分离
- 生成最小但可用的测试骨架（
unit/registry/smoke）
Default families:
generatefilterrefineeval
Two Working Modes
Mode A: Interactive Interview Mode
Use AskUserQuestion in batch mode with exactly two rounds:
Use structured questioning in batch mode with exactly two rounds:
- Round 1: structure fields
- Round 2: implementation fields
Important:
- In each question block, include recommended option + short reason.
- Ask follow-up questions only when high-impact fields are missing or contradictory.
- Do not ask one-by-one when the same round can be asked in one batch.
- Present all questions of one round in a single message to the user, grouped by round.
What ships with it
21 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.
- assets/templates/cli/operator_cli.py.tmpl 2.9 KB
- assets/templates/operators/eval_operator.py.tmpl 2.4 KB
- assets/templates/operators/filter_operator.py.tmpl 1.5 KB
- assets/templates/operators/generate_operator.py.tmpl 2.3 KB
- assets/templates/operators/refine_operator.py.tmpl 2.3 KB
- assets/templates/package/cli_init.py.tmpl 46 B
- assets/templates/package/operator_pkg_init.py.tmpl 140 B
- assets/templates/package/operators_root_init.py.tmpl 49 B
- assets/templates/package/package_init.py.tmpl 476 B
- assets/templates/tests/test_operator_registry.py.tmpl 417 B
- assets/templates/tests/test_operator_smoke.py.tmpl 1.8 KB
- assets/templates/tests/test_operator_unit.py.tmpl 2.1 KB
- references/acceptance-checklist.md 1.2 KB
- references/askuserquestion-rounds.md 2.8 KB
- references/cli-shell-guidelines.md 1.2 KB
- references/gotchas.md 3.2 KB
- references/operator-contract.md 1.4 KB
- references/output-checklist.md 733 B
- references/registration-rules.md 991 B
- scripts/build_operator_artifacts.py 26 KB runs code
- scripts/example_spec.json 428 B
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 First seen · 267 lines · 66 tokens per session scan A 602980a26897
dataflow-operator-builder is a skill published in the GitHub repository OpenDCAI/DataFlow-WebUI (253 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 66 tokens to every session and 2,078 once invoked, about $0.0003 per session on Opus 5.5. 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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