agentmods.dev

core_text

A reference package documenting DataFlow operators for generating, filtering, refining, and evaluating text. DataFlow is a system for processing datasets through connected steps called pipelines.

In plain words
What is it for?
Use it to look up supported operators, their inputs and outputs, and common usage mistakes.
Why use it?
It provides the exact instructions needed when a pipeline requires an operator beyond the basic set.

Skill for Claude CodeCodex

224 +4 7d ago A scan 68 tokens original Apache-2.0
View the source file OpenDCAI/DataFlow-WebUI
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/opendcai/dataflow-webui/core_text
Any agent
npx skills add OpenDCAI/DataFlow-WebUI --skill core_text
Clone the repo
git clone --depth 1 https://github.com/OpenDCAI/DataFlow-WebUI

Made for: Claude Code, Codex.

Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 664 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 $0.00068 $0.00664
Opus 5 $0.00034 $0.00332
Sonnet 5 $0.00014 $0.00133
Haiku 4.5 $0.00007 $0.00066

Measured 2d ago against content hash 7d1e09b10673, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

core_text 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/canonical/core_text/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

core_text operator reference

Per-operator API documentation for DataFlow's core_text family. Consult it when you need an operator's exact constructor and run() signature, its real row-processing behaviour, or the mistakes that break it.

Do not invoke this as a skill. There is no workflow here. The generating-dataflow-pipeline skill reads these files when it needs an operator beyond its six core primitives.

Layout

core_text/<category>/<operator>/
├── SKILL.md            English reference: constructor, run(), execution logic,
│                       mandatory rules, return-value semantics
├── SKILL_zh.md         Chinese translation
└── examples/
    ├── good.md         Best-practice pipeline usage
    └── bad.md          Common mistakes and how they fail

What is documented

Category Path Operators
Generate generate/ PromptedGenerator, FormatStrPromptedGenerator, Text2MultiHopQAGenerator, BenchAnswerGenerator, ChunkedPromptedGenerator, EmbeddingGenerator, RandomDomainKnowledgeRowGenerator, RetrievalGenerator
Filter filter/ GeneralFilter, KCenterGreedyFilter, PromptedFilter
Refine refine/ PandasOperator, PromptedRefiner
Eval eval/ BenchDatasetEvaluator, BenchDatasetEvaluatorQuestion, PromptedEvaluator, Text2QASampleEvaluator, UnifiedBenchDatasetEvaluator

How to use it

  1. Find the operator's directory under its category.
  2. Read its SKILL.md for the authoritative signature.
  3. Check that operator's bad.md example before writing code — it documents the failure modes that come up most often.

Accuracy and scope

These are static reference docs, aligned to a specific DataFlow version (recorded in VERSION.md in this directory). They are not a live query.

When an MCP server is available, get_operator_detail_by_name is authoritative: it reflects the operators actually installed. Prefer it, and treat a disagreement with these files as this reference being out of date.

Read the full file on GitHub · 64 lines

Files

What ships with it

60 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 · 64 lines · 68 tokens per session scan A 7d1e09b10673

Subscribe to this mod's changes

core_text is a skill published in the GitHub repository OpenDCAI/DataFlow-WebUI (224 stars, last pushed 7d ago), licensed Apache-2.0. It adds 68 tokens to every session and 664 once invoked, about $0.0003 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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