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 opendatahub-io/ai-helpers --skill doc-pipelinegit clone --depth 1 https://github.com/opendatahub-io/ai-helpersWrote 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/opendatahub-io/ai-helpers/doc-pipeline)<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/doc-pipeline"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/doc-pipeline/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/opendatahub-io/ai-helpers/doc-pipeline"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/doc-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 Data Exfiltration · line 26 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
- medium Excessive Agency · line 8 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00043 | $0.01053 |
| Opus 5 | $0.00022 | $0.00526 |
| Sonnet 5 | $0.00009 | $0.00211 |
| Haiku 4.5 | $0.00004 | $0.00105 |
Grade A, and why
doc-pipeline 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 12d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
doc-pipeline
Orchestrate documentation skills in dependency order based on the requested pipeline mode.
Parse arguments
$ARGUMENTS contains:
- Jira key or PR URL: the feature identifier (required)
- Mode: one of
gather,gap,validate,review,generate(required)
Pipeline Modes
| Mode | Skills executed | Use case |
|---|---|---|
gather |
doc-gather | Collect context only |
gap |
doc-gather → doc-gap | Identify documentation gaps |
validate |
doc-gather → doc-validate | Validate existing docs against context |
review |
doc-gather → doc-validate → doc-review | Full validation and review of existing docs |
generate |
doc-gather → doc-gap → doc-generate → doc-validate → doc-review | Generate docs end-to-end |
Execution Protocol
Step 1: Validate inputs
- Confirm the Jira key or PR URL is provided
- Confirm the mode is one of the valid options
- Check that
${CLAUDE_SKILL_DIR}/../doc-gather/configs/rhoai.yamlexists
Step 2: Execute skills in order
For each skill in the pipeline mode's sequence:
- Announce the current phase to the caller
- Invoke the skill using
/doc-<skill> <arguments> - Check the skill output:
- If the skill produced an output file, verify it exists
- If the skill reported errors, decide whether to continue or halt
- Route outputs to the next skill (via workspace files)
Skill invocations by mode
mode: gather
/doc-gather <JIRA-KEY>
Report: context package summary.
mode: gap
/doc-gather <JIRA-KEY>
/doc-gap
Check: if gap report recommendation is stop, halt and report gaps to caller.
Report: gap report summary.
mode: validate
/doc-gather <JIRA-KEY>
/doc-validate <docs-directory>
The docs directory is determined from the context package (the docs repo checkout path). Report: validation findings summary.
mode: review
/doc-gather <JIRA-KEY>
/doc-validate <docs-directory>
/doc-review <docs-directory>
Report: validation + review findings summary.
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.
- 12d ago First seen · 140 lines · 43 tokens per session scan A 2871957ac48e
doc-pipeline is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed 5d ago), licensed Apache-2.0. It adds 43 tokens to every session and 1,053 once invoked, about $0.0002 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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