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 agentmods add skills/timurgaleev/vibestack/document-generatenpx skills add timurgaleev/vibestack --skill document-generategit clone --depth 1 https://github.com/timurgaleev/vibestackWrote 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/timurgaleev/vibestack/document-generate)<a href="https://agentmods.dev/skills/timurgaleev/vibestack/document-generate"><img src="https://agentmods.dev/badge/skills/timurgaleev/vibestack/document-generate.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00058 | $0.04501 |
| Opus 5 | $0.00029 | $0.02250 |
| Sonnet 5 | $0.00012 | $0.00900 |
| Haiku 4.5 | $0.00006 | $0.00450 |
Grade A, and why
document-generate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 522 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to invoke
Use when asked to "write docs", "generate documentation", "document this feature", "create a tutorial", or "explain this module".
Preamble
eval "$(~/.vibestack/bin/vibe-slug 2>/dev/null)" 2>/dev/null || SLUG="unknown"
_LEARN_FILE="${VIBESTACK_HOME:-$HOME/.vibestack}/projects/${SLUG:-unknown}/learnings.jsonl"
if [ -f "$_LEARN_FILE" ]; then
_LEARN_COUNT=$(wc -l < "$_LEARN_FILE" 2>/dev/null | tr -d ' ')
echo "LEARNINGS: $_LEARN_COUNT entries loaded"
if [ "$_LEARN_COUNT" -gt 5 ] 2>/dev/null; then
~/.vibestack/bin/vibe-learnings-search --limit 5 2>/dev/null || true
fi
else
echo "LEARNINGS: none yet"
fi
{{include lib/snippets/session-host.md}}
{{include lib/snippets/decision-brief.md}}
{{include lib/snippets/working-protocols.md}}
{{include lib/snippets/state-protocols.md}}
Step 0: Detect base branch
Determine which branch this work targets, or the repo's default branch. Probes
GitHub (gh) and GitLab (glab) before the git-native fallback, so the base is
correct on either host:
BASE=$(gh pr view --json baseRefName -q .baseRefName 2>/dev/null)
[ -z "$BASE" ] && BASE=$(glab mr view -F json 2>/dev/null \
| python3 -c "import sys,json; print(json.load(sys.stdin).get('target_branch',''))" 2>/dev/null)
[ -z "$BASE" ] && BASE=$(git symbolic-ref refs/remotes/origin/HEAD 2>/dev/null | sed 's|refs/remotes/origin/||')
[ -z "$BASE" ] && git rev-parse --verify origin/main >/dev/null 2>&1 && BASE=main
[ -z "$BASE" ] && git rev-parse --verify origin/master >/dev/null 2>&1 && BASE=master
[ -z "$BASE" ] && BASE=main
echo "Base branch: $BASE"
Use $BASE in subsequent git diff / git log commands.
Document Generate: Diataxis Documentation Writer
You are running the /document-generate workflow. Your job: produce high-quality,
structured documentation for features, modules, or an entire project. You research
the code thoroughly before writing a single line of documentation.
This skill can be invoked two ways:
- Standalone — the user points you at a feature, module, or project and says "document this"
- From /document-release — the coverage map identified gaps; you fill them
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.
- today Changed · +19 lines 6e54145d5f13
- 4d ago First seen · 503 lines · 58 tokens per session scan A 326819c924e4
document-generate is a skill published in the GitHub repository timurgaleev/vibestack (6 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 4,501 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 2026-08-31.
Other skills, from other repositories
explain-for
Explain a topic, a piece of code, an error, or a design decision calibrated to one named audience — a 5-year-old, a 5th grader, a manager, a designer, a graduate student, a parent. Resolves who the explanation is for (from the request, or from what memory already records about that person), establishes the ground…
1c-help-mcp
Этот скилл MUST быть вызван для поиска по документации платформы 1С — методы, функции, синтаксис, API. SHOULD также вызывать перед написанием BSL-кода для проверки синтаксиса метода. Do NOT использовать для поиска паттернов БСП — используй bsp-patterns.
interview
AI-native interview platform. Type /interview to start a candidate session — captures all prompts, responses, tool calls, and file changes. Type /submit to end the session, seal the log, and send the full thought-process audit to the hiring manager.
article-writing
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
mochi-remind
Handle due reminders — notify the user with natural language and mark them done.
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.