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 prompted-filtergit 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/prompted-filter)<a href="https://agentmods.dev/skills/opendcai/dataflow-webui/prompted-filter"><img src="https://agentmods.dev/badge/skills/opendcai/dataflow-webui/prompted-filter/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/prompted-filter"><img src="https://agentmods.dev/badge/skills/opendcai/dataflow-webui/prompted-filter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
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 →
- medium Prompt Injection · line 31 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 55 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Data Exfiltration · line 100 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00047 | $0.01101 |
| Opus 5.5 | $0.00019 | $0.00440 |
| Sonnet 5.5 | $0.00009 | $0.00220 |
| Haiku 4.5 | $0.00005 | $0.00110 |
Grade A, and why
prompted-filter 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PromptedFilter Operator Reference
PromptedFilter internally uses PromptedEvaluator to score each row of text, writes the score into output_key, and keeps only rows with scores in [min_score, max_score].
1. Import
from dataflow.operators.core_text import PromptedFilter
2. Constructor
PromptedFilter(
llm_serving,
system_prompt="Please evaluate the quality of this data on a scale from 1 to 5.",
min_score=1,
max_score=5,
)
| Parameter | Required | Default | Description |
|---|---|---|---|
llm_serving |
Yes | None | LLM service object implementing generate_from_input(...). Internally passed to PromptedEvaluator. |
system_prompt |
No | "Please evaluate the quality of this data on a scale from 1 to 5." |
Defines the LLM's scoring criteria. The scale described should align with min_score/max_score. |
min_score |
No | 1 |
Lower bound of the score range to keep (inclusive). |
max_score |
No | 5 |
Upper bound of the score range to keep (inclusive). |
Important Constructor Notes
- The operator creates an internal
PromptedEvaluator(llm_serving, system_prompt)instance. - Source code comment at line 35 incorrectly states
min_scoredefault is5; actual default is1. - Source code comment at line 36 incorrectly states
max_scoredefault is5; actual default is5(correct).
What ships with it
3 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.
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 · 126 lines · 47 tokens per session scan A 297a28244937
prompted-filter is a skill published in the GitHub repository OpenDCAI/DataFlow-WebUI (253 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 47 tokens to every session and 1,101 once invoked, about $0.0002 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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