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.
git clone --depth 1 https://github.com/steipete/agent-rulesWrote 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/rules/steipete/agent-rules/github-issue-creation)<a href="https://agentmods.dev/rules/steipete/agent-rules/github-issue-creation"><img src="https://agentmods.dev/badge/rules/steipete/agent-rules/github-issue-creation/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/rules/steipete/agent-rules/github-issue-creation"><img src="https://agentmods.dev/badge/rules/steipete/agent-rules/github-issue-creation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00015 | $0.00614 |
| Opus 5.5 | $0.00006 | $0.00246 |
| Sonnet 5.5 | $0.00003 | $0.00123 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
github-issue-creation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- github-issue-creation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Issue Creation
Credit: This rule is based on instructions by @nityeshaga (https://x.com/nityeshaga/status/1933113428379574367)
You are an AI assistant tasked with creating well-structured GitHub issues for feature requests, bug reports, or improvement ideas. Your goal is to turn the provided feature description into a comprehensive GitHub issue that follows best practices and project conventions.
First, you will be given a feature description and a repository URL. Here they are:
<feature_description> #$ARGUMENTS </feature_description>
Follow these steps to complete the task, make a todo list and think ultrahard:
1. Research the repository:
- Visit the provided repo url and examine the repository's structure, existing issues, and documentation.
- Look for any CONTRIBUTING.md, ISSUE_TEMPLATE.md, or similar files that contain guidelines for creating issues.
- Note the project's coding style, naming conventions, and any specific requirements for submitting issues.
2. Research best practices:
- Search for current best practices in writing GitHub issues, focusing on clarity, completeness, and actionability.
- Look for examples of well-written issues in popular open-source projects for inspiration.
3. Present a plan:
- Based on your research, outline a plan for creating the GitHub issue.
- Include the proposed structure of the issue, any labels or milestones you plan to use, and how you'll incorporate project-specific conventions.
- Present this plan in tags.
- Include the reference link to featurebase or any other link that has the source of the user request *K for Command, *L for Cascade
4. Create the GitHub issue:
- Once the plan is approved, draft the GitHub issue content.
- Include a clear title, detailed description, acceptance criteria, and any additional context or resources that would be helpful for developers.
- Use appropriate formatting (e.g., Markdown) to enhance readability.
- Add any relevant labels, milestones, or assignees based on the project's conventions.
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.
- 1mo ago First seen · 47 lines · 15 tokens per session scan A 2b9c93cacd96
github-issue-creation is a cursor rule published in the GitHub repository steipete/agent-rules (5,677 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 614 once invoked, about $0.0001 per session on Opus 5.5. 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 cursor rules, from other repositories
WORKFLOW
Staged spec→plan→coding→review workflow with shared task state on disk.
cc
You are Code Captain - a methodical AI development partner who executes comprehensive software workflows. You organize all work in .code-captain/ folders and use todowrite for progress tracking.
_project-jira
ALWAYS READ THIS to obtain Jira information.
project-epic-template-cursorrules-prompt-file
Cursor rules for project development with epic template integration.
monorepo-and-tooling
Rules for projects that may use a monorepo, a single repository containing multiple applications or shared packages. They also define Taskfile commands and how to keep environment settings outside the code.
swamr-state-manager
Swamr State Manager — tracks task progress, manages the execution pipeline, handles retries and escalation. Maintains swamr/state.json as the single source of truth for swarm progress.