Qwen Code is an open-source AI coding agent that runs in a terminal and helps developers work with code through language models. It supports multiple model providers and can also be used through IDEs, desktop software, SDKs, and messaging bots.
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/goal-draftnpx skills add QwenLM/qwen-code --skill goal-draftgit clone --depth 1 https://github.com/QwenLM/qwen-codeWrote 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/skills/qwenlm/qwen-code/goal-draft)<a href="https://agentmods.dev/skills/qwenlm/qwen-code/goal-draft"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-code/goal-draft.svg" alt="Measured on agentmods" 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 | $0.00114 | $0.02037 |
| Opus 5 | $0.00057 | $0.01019 |
| Sonnet 5 | $0.00023 | $0.00407 |
| Haiku 4.5 | $0.00011 | $0.00204 |
Grade A, and why
goal-draft 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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/goal-draft — write a Goal the verifier can judge
You are already inside the loaded goal-draft skill — do not call the skill tool to invoke it again; start with Step 0.
You are drafting the text for /goal set. You are NOT doing the work the goal describes. Do not edit files, do not run the checks, do not start on the task. The only deliverable is the objective text and the /goal set line the user can run.
How Goals are judged (why the format below matters)
An active Goal is re-fed to the model every turn, and its completion is judged by an independent verifier that sees ONLY transcript evidence:
- Visible assistant output and tool results count as evidence. The objective itself, user prompts, and hidden reasoning do not.
delivered_outputevidence proves only that text was printed. It cannot prove that tests passed, files changed, or remote state changed — those need a tool result in the transcript (anexternal_fact).- A claim that the user confirmed, chose, or approved something needs a real user message as evidence; otherwise the completion proposal is rejected.
- Vague, subjective, or open-ended conditions never accumulate enough evidence; the loop then runs until a limit is hit.
So a good objective makes the agent PRODUCE evidence: run the named check and paste the decisive output line.
Step 0 — should this be a Goal at all?
Say no, briefly, when the request is a normal one-shot task, needs a design or product judgement call, or has no way to be checked from the agent's own output. Offer to just do it, or to write a plan instead. A goal that cannot be checked is a prompt, not a goal.
Step 1 — check the active Goal
Call get_goal. If a Goal is active, ask whether to edit it (same goal, tighter wording → /goal edit) or replace it (/goal set). Never draft a second concurrent goal.
Step 2 — ground the draft in the workspace
Before asking anything, verify what you can with read_file, glob, and grep_search: that named files and packages exist, and what the real check commands are (package.json scripts, Makefile, CI workflow, test config). Use those exact commands in "Done when". Never invent paths, IDs, or commands; write <TODO: …> for anything you cannot confirm.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago Changed · +4 lines c312ea36190b
- 5d ago First seen · 110 lines · 114 tokens per session scan A 50bfc069718e
goal-draft is a skill published in the GitHub repository QwenLM/qwen-code (27,620 stars, last pushed yesterday), licensed Apache-2.0. It adds 114 tokens to every session and 2,037 once invoked, about $0.0006 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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