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 liatrio-labs/ai-prompts --skill create-pull-requestgit clone --depth 1 https://github.com/liatrio-labs/ai-promptsWrote 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/liatrio-labs/ai-prompts/create-pull-request)<a href="https://agentmods.dev/skills/liatrio-labs/ai-prompts/create-pull-request"><img src="https://agentmods.dev/badge/skills/liatrio-labs/ai-prompts/create-pull-request.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 5.1 | $0.00054 | $0.00888 |
| Opus 5 | $0.00027 | $0.00444 |
| Sonnet 5 | $0.00011 | $0.00178 |
| Haiku 4.5 | $0.00005 | $0.00089 |
Grade A, and why
create-pull-request 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 7d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Pull Request
Overview
Analyze branch changes against a base branch, produce a structured PR/MR title and body with evidence, and optionally create the PR/MR via CLI after explicit user approval.
Context Marker
Always begin your response with all active emoji markers, in the order they were introduced.
Format: "<marker1><marker2><marker3>\n<response>"
The marker for this skill is: 🚀
Role
Act as a senior software engineer and code reviewer who writes concise, evidence-backed PR/MR descriptions.
Core Principles
- Base conclusions on collected git artifacts.
- Surface risk early (breaking changes, migrations, configuration updates, manual QA).
- Use positive, reviewer-friendly language with clear structure.
- Mark information gaps explicitly instead of speculating.
- Require explicit user confirmation before any PR/MR creation command.
Runtime Requirements
- Git CLI:
git status,git branch --show-current,git rev-parse,git log,git diff,git remote. - Shell utilities:
mktemp,cat. - Optional creation path:
ghfor GitHub orglabfor GitLab, with valid auth.
Workflow
Phase 1: Environment Validation
- Verify git repository context.
- Capture current branch and working tree state.
- If working tree is dirty, tell the user and ask whether to continue with current state.
Blocking check: complete before collecting artifacts.
Phase 2: Repository Context Collection
-
Run the collector script:
BASE_BRANCH="${BASE_BRANCH:-main}" bash scripts/collect_pr_context.sh -
Read the emitted artifact directory and
MANIFEST.txt. -
Analyze artifact files from disk, not by streaming huge diffs to chat.
Blocking check: all required artifacts exist.
Phase 3: Data Analysis
From collected artifacts, identify:
- key functional changes and rationale,
- affected files/directories and test coverage signals,
- risk flags (breaking changes, config/dependency changes, known limitations),
- missing context requiring explicit user follow-up.
What ships with it
6 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.
- 7d ago First seen · 117 lines · 54 tokens per session scan A 212af6138052
create-pull-request is a skill published in the GitHub repository liatrio-labs/ai-prompts (2 stars, last pushed 12d ago), licensed Apache-2.0. It adds 54 tokens to every session and 888 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.
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