Borrowing it
Nothing to install: this file belongs to wbern/agent-instructions. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/wbern/agent-instructions/main/.claude/commands/create-issues.mdgit clone --depth 1 https://github.com/wbern/agent-instructionsWrote 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/commands/wbern/agent-instructions/create-issues)<a href="https://agentmods.dev/commands/wbern/agent-instructions/create-issues"><img src="https://agentmods.dev/badge/commands/wbern/agent-instructions/create-issues/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/commands/wbern/agent-instructions/create-issues"><img src="https://agentmods.dev/badge/commands/wbern/agent-instructions/create-issues.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 | $0.00018 | $0.01320 |
| Opus 5.5 | $0.00007 | $0.00528 |
| Sonnet 5.5 | $0.00004 | $0.00264 |
| Haiku 4.5 | $0.00002 | $0.00132 |
Grade A, and why
create-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 2mo 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 — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Issues: PRD-Informed Task Planning for TDD
Create structured implementation plan that bridges product thinking (PRD) with test-driven development.
General Guidelines
Output Style
- Never explicitly mention TDD in code, comments, commits, PRs, or issues
- Write natural, descriptive code without meta-commentary about the development process
- The code should speak for itself - TDD is the process, not the product
Beads is available for task tracking. Use mcp__beads__* tools to manage issues (the user interacts via bd commands).
Plan File Restriction
NEVER create, read, or update plan.md files. Claude Code's internal planning files are disabled for this project. Use other methods to track implementation progress (e.g., comments, todo lists, or external tools).
User arguments:
Create-issues: $ARGUMENTS
End of user arguments
(If no input provided, check conversation context or run bd ready to see existing work)
Input Processing
The input can be one of:
- GitHub Issue URL (e.g.,
https://github.com/owner/repo/issues/123) - GitHub Issue Number (e.g.,
#123or123) - Feature Description (e.g., "Add user authentication")
- Empty - use conversation context
GitHub Issue Integration
If input looks like a GitHub issue:
Step 1: Extract Issue Number
- From URL: extract owner/repo/number
- From number: try to infer repo from git remote
- From branch name: check patterns like
issue-123,123-feature,feature/123
Step 2: Fetch Issue
Try to fetch the issue using GitHub MCP (mcp__github__issue_read tool).
If GitHub MCP is not configured, show:
GitHub MCP not configured!
See: https://github.com/modelcontextprotocol/servers/tree/main/src/github
Trying GitHub CLI fallback...
Then try using gh issue view [ISSUE_NUMBER] --json as fallback.
Step 3: Use Issue as Discovery Input
- Title → Feature name
- Description → Problem statement and context
- Labels → Type/priority hints
- Comments → Additional requirements and discussion
- Linked issues → Dependencies
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.
- 2mo ago First seen · 206 lines · 18 tokens per session scan A a35145e0bff8
create-issues is a command published in the GitHub repository wbern/agent-instructions (168 stars, last pushed 5mo ago), licensed MIT. It adds 18 tokens to every session and 1,320 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.