issues

A command for turning a feature request, bug report, or improvement idea into a structured GitHub issue. GitHub issues are records used to discuss and track work in a repository.

In plain words
What is it for?
Use it to research a repository’s contribution rules and create an issue that follows its conventions and relevant issue-writing practices.
Why use it?
It helps produce issues with enough context and structure for other contributors to understand and act on them.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/hint-services/obsidian-github-mcp/issues
Clone the repo
git clone --depth 1 https://github.com/Hint-Services/obsidian-github-mcp

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 510 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00510
Opus 5 $0.00000 $0.00255
Sonnet 5 $0.00000 $0.00102
Haiku 4.5 $0.00000 $0.00051

Measured 2d ago against content hash 801ed951a691, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

issues 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 2d 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.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

  • issues — 100% identical, 0 lines differ
  • issues — 100% identical, 0 lines differ
  • issues — 100% identical, 0 lines differ
.claude/commands/issues.md · 43 lines

What it actually says

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 might 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.
  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.
  5. Final output:

    • Present the complete GitHub issue content in <github_issue> tags.
    • Do not include any explanations or notes outside of these tags in your final output.

Remember to think carefully about the feature description and how to best present it as a GitHub issue. Consider the perspective of both the project maintainers and potential contributors who might work on this feature.

Your final output should consist of only the content within the <github_issue> tags, ready to be copied and pasted directly into GitHub. Make sure to use the GitHub CLI gh issue create to create the actual issue after you generate. Assign either the label bug or enhancement based on the nature of the issue.

Changes

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.

  1. 2d ago First seen · 43 lines · 0 tokens per session scan A 801ed951a691

Subscribe to this mod's changes

issues is a command published in the GitHub repository Hint-Services/obsidian-github-mcp (9 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 510 tokens. 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.