issue-create

A command for creating a structured GitHub issue from a description or the current project context. GitHub issues are records used to track bugs, tasks, and feature requests.

In plain words
What is it for?
Use it to record bugs, deferred review findings, refactoring work, feature ideas, or other tracked tasks in a GitHub repository.
Why use it?
It turns informal notes into an issue with the relevant template, labels, assignee, and project context when those details are available.

Command

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/leanandmean/mach10/issue-create
Clone the repo
git clone --depth 1 https://github.com/LeanAndMean/mach10
Per session 11 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,006 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 $0.00011 $0.02006
Opus 5 $0.00005 $0.01003
Sonnet 5 $0.00002 $0.00401
Haiku 4.5 $0.00001 $0.00201

Measured 2d ago against content hash aadbd7ee8619, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

issue-create 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.

commands/issue-create.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create Issue

You are creating a structured GitHub issue. This may be invoked at any point in the workflow — to capture deferred review findings, document refactoring needs, or track new feature ideas.

Context (optional): $ARGUMENTS

Step 1: Gather Context

If context was provided ($ARGUMENTS), parse it for two kinds of input and act on each:

  • Descriptive content (problem statement, feature description, observed behavior, motivation): Use as the starting point for drafting the issue body in Step 2.
  • Meta-directives about the issue itself (e.g., "use the bug template", "tag as priority-high", "assign me", "make this a tracking issue"): Note these for the appropriate downstream step. Template choice steers the template selection later in this step. Labels and assignees are applied via gh issue create / gh issue edit flags in Step 5. Honor meta-directives explicitly -- do not fold them into the issue body as descriptive text.

If no context was provided, ask the user what the issue is about.

Check if the repository has issue templates:

ls .github/ISSUE_TEMPLATE/ 2>/dev/null

If templates exist, read them and select the most appropriate one. If no templates, use the standard format below.

Step 2: Draft the Issue

Draft a structured issue with these sections:

Title

  • Clear, concise, actionable (under 80 characters)
  • Use imperative form (e.g., "Add validation for bulk solvent inputs")

Body

  • Summary: 2-3 sentences describing the problem or feature
  • Current Behavior (for bugs/improvements): What happens now
  • Proposed Behavior: What should happen -- describe desired outcomes rather than implementation steps. If the issue's subject is a command definition, agent definition, or workflow specification, naming the specific file and section as the target of a behavioral change is appropriate here; move to Technical Notes only when describing the mechanism of the change (algorithm, control flow, data structure choices).
  • Acceptance Criteria: Bullet list of verifiable end-state conditions that define "done", independent of implementation approach. Exception: when the artifact being changed is itself a specification (command definitions, config schemas, workflow files, documentation), implementation-specific criteria are appropriate because the spec IS the implementation.
  • Context (optional): Links to related PRs, issues, or discussions
  • Technical Notes (optional): Implementation hints, relevant files, architectural considerations

Read the full file on GitHub · 144 lines

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 · 144 lines · 11 tokens per session scan A aadbd7ee8619

Subscribe to this mod's changes

issue-create is a command published in the GitHub repository LeanAndMean/mach10 (20 stars, last pushed 3mo ago), licensed MIT. It adds 11 tokens to every session and 2,006 once invoked, about $0.0001 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.