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 agentmods add skills/qwenlm/qwen-code/create-issuenpx skills add QwenLM/qwen-code --skill create-issuegit clone --depth 1 https://github.com/QwenLM/qwen-codeWhat 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 | $0.00026 | $0.00507 |
| Opus 5 | $0.00013 | $0.00253 |
| Sonnet 5 | $0.00005 | $0.00101 |
| Haiku 4.5 | $0.00003 | $0.00051 |
Grade A, and why
create-issue 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 3d 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.
What it actually says
Create Issue
Take the user's idea or bug description, investigate the codebase for context, draft an issue for review, and submit once approved.
Input
The user provides a brief description of a feature request or bug report via the skill argument.
Steps
1. Classify
Determine whether the request is a feature request or a bug report.
2. Investigate the codebase
Search for relevant code, files, and existing behavior related to the request.
Build a thorough understanding of how the current system works. Note any related
existing issues found via gh issue list --search.
3. Read the template
- Feature request → read
.github/ISSUE_TEMPLATE/feature_request.yml - Bug report → read
.github/ISSUE_TEMPLATE/bug_report.yml
Use the template's field labels and descriptions to structure the draft.
4. Draft the issue
Write a markdown draft to .qwen/issues/draft-<slug>.md for the user to review.
Rules:
-
Write from the user's perspective — not as an implementation spec.
-
Keep language clear and concise; avoid internal implementation details.
-
Title stays in English only.
-
Bilingual body: English content first, Chinese translation at the end wrapped in a collapsible block:
<details> <summary>中文</summary> (Chinese translation here) </details>
5. Review with user
Present the draft. Iterate on feedback until the user is satisfied. Do not submit until the user explicitly approves.
6. Submit
When the user confirms, create the issue with gh issue create:
gh issue create --title "..." --body-file .qwen/issues/draft-<slug>.md
Apply labels based on type:
- Feature request →
type/feature-request,status/needs-triage - Bug report →
type/bug,status/needs-triage
Report the issue URL back to the user.
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.
- 3d ago First seen · 82 lines · 26 tokens per session scan A 5e2975e11519
create-issue is a skill published in the GitHub repository QwenLM/qwen-code (27,559 stars, last pushed yesterday), licensed Apache-2.0. It adds 26 tokens to every session and 507 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.
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