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-plangit 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-plan)<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/doc-plan"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/doc-plan/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-plan"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/doc-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 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 | $0.00041 | $0.01203 |
| Opus 5 | $0.00020 | $0.00602 |
| Sonnet 5 | $0.00008 | $0.00241 |
| Haiku 4.5 | $0.00004 | $0.00120 |
Grade A, and why
doc-plan 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
doc-plan
Produce a documentation plan for a strategic initiative (STRAT) or epic by analyzing all child tickets for documentation impact.
Parse arguments
$ARGUMENTS contains a Jira ticket key, typically a STRAT-level or epic-level ticket (e.g., RHAISTRAT-1401 or RHOAIENG-55000).
Step 1: Resolve the root ticket
Call the MCP tool to resolve the ticket:
mcp__mcp-atlassian__jira_get_issue(issue_key="<KEY>")
Extract:
- Summary, description, status
- Issue type (Initiative, Epic, Story)
- Fix versions
- Child tickets / linked tickets
Step 2: Traverse child hierarchy
Resolve all child tickets recursively (up to 3 levels deep):
- STRAT/Initiative → child Epics
- Epic → child Stories/Tasks
- Story → sub-tasks (if any)
For each ticket, resolve via MCP and extract:
- Key, summary, description, status, issue type
- Components
- Fix versions
- Labels
Cycle detection: maintain a visited set of issue keys during traversal. Before descending into any child ticket, check whether its key is already in the visited set. If so, skip that branch and record that a cycle was detected.
Limits:
- Depth cap: 3 levels maximum
- Global cap: resolve up to 100 child tickets. If more exist, note the truncation.
- If either cap is reached, stop further traversal and note the truncation in the output.
Step 3: Assess documentation impact
For each resolved child ticket, determine:
-
Does this ticket affect documentation?
- Read the summary and description
- Check if it introduces user-visible changes
- Check components (documentation-relevant components vs internal)
- Look for keywords: "API", "config", "parameter", "UI", "workflow", "deprecate"
-
What type of documentation is needed?
- Map to: new_concept, new_procedure, new_reference, update_existing, release_note, deprecation_notice, none
-
What priority?
- critical: mentioned in acceptance criteria, GA-blocking
- high: significant user-facing change
- medium: improvement, enhancement
- low: minor change, edge case
What ships with it
1 file 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.
- 12d ago First seen · 172 lines · 41 tokens per session scan A 101b95bafaf7
doc-plan is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed 5d ago), licensed Apache-2.0. It adds 41 tokens to every session and 1,203 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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