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-postgit 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-post)<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/doc-post"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/doc-post/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-post"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/doc-post.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 | $0.00037 | $0.00800 |
| Opus 5 | $0.00018 | $0.00400 |
| Sonnet 5 | $0.00007 | $0.00160 |
| Haiku 4.5 | $0.00004 | $0.00080 |
Grade A, and why
doc-post 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 10d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
doc-post
Post validation and review findings as comments on a PR/MR.
Parse arguments
$ARGUMENTS contains:
- PR URL: GitHub or GitLab PR/MR URL (required)
- Flags (optional):
--validation: post validation findings only--review: post review findings only--all(default): post both validation and review findings
Step 1: Detect platform
From the PR URL, determine the platform:
github.com→ GitHub (useghCLI)- Other → GitLab (use GitLab API)
Step 2: Load findings
Based on flags, read the relevant findings files:
- Validation:
workspace/validation-findings.json - Review:
workspace/review-findings.json
If a requested file doesn't exist, warn and skip it.
Step 3: Format comments
Summary comment
Create a summary comment with an overview table:
## Documentation Review Results
| Category | High | Medium | Low | Total |
|----------|------|--------|-----|-------|
| Validation | 0 | 3 | 5 | 8 |
| Review | 1 | 2 | 3 | 6 |
| **Total** | **1** | **5** | **8** | **14** |
**Review confidence**: 0.78
### High-severity findings
1. **[ref_model-serving-params.adoc:42]** Technical inaccuracy: The documented API field 'replicas' should be 'minReplicas'
- **Suggestion**: Change 'replicas' to 'minReplicas' per the CRD type definition
### Medium-severity findings
1. **[con_model-serving.adoc:15]** Vale: Use 'Red Hat OpenShift AI' instead of 'RHOAI' on first reference
Inline comments (GitHub only)
For findings that reference specific files and lines in the PR's changed files:
- Get the list of changed files:
gh pr view <URL> --json files - For each finding that references a changed file, post an inline review comment
- For findings in files not in the PR diff, include them in the summary comment
Step 4: Post comments
GitHub
# Post summary comment
gh pr comment <PR-URL> --body "<summary>"
# Post inline review (if applicable)
gh api repos/{owner}/{repo}/pulls/{number}/reviews \
--method POST \
--field body="Documentation review complete" \
--field event="COMMENT" \
--field comments="[...]"
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.
- 10d ago First seen · 112 lines · 37 tokens per session scan A ea76ddd2cebf
doc-post is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed 2d ago), licensed Apache-2.0. It adds 37 tokens to every session and 800 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.
Other skills, from other repositories
github-automation
GitHub workflow automation, PR management, issue tracking, and code review coordination. Integrates with GitHub Actions and repository management. Use when: PR creation, code review, issue management, release automation, workflow setup. Skip when: local-only changes, non-GitHub repositories.
code-review-excellence
Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
multi-reviewer-patterns
Coordinate parallel code reviews across multiple quality dimensions with finding deduplication, severity calibration, and consolidated reporting. Use this skill when organizing multi-reviewer code reviews, calibrating finding severity, or consolidating review results.
git-advanced-workflows
Master advanced Git workflows including rebasing, cherry-picking, bisect, worktrees, and reflog to maintain clean history and recover from any situation. Use when managing complex Git histories, collaborating on feature branches, or troubleshooting repository issues.
workflow-patterns
Use this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.
gentle-ai-collab-perfect
Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the…