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 commands/duncanyoung-1/auto-embedded/continuegit clone --depth 1 https://github.com/DunCanYounG-1/auto-embeddedWrote 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/duncanyoung-1/auto-embedded/continue)<a href="https://agentmods.dev/commands/duncanyoung-1/auto-embedded/continue"><img src="https://agentmods.dev/badge/commands/duncanyoung-1/auto-embedded/continue.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 | $0.00000 | $0.00326 |
| Opus 5 | $0.00000 | $0.00163 |
| Sonnet 5 | $0.00000 | $0.00065 |
| Haiku 4.5 | $0.00000 | $0.00033 |
Grade A, and why
continue 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 4d 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
{{CMD_REF:continue}} —— 继续当前任务
恢复现场,按 RIPER 阶段在正确的步骤接着干。
1. 载入现场
{{PYTHON_CMD}} .auto-embedded/scripts/get_context.py
确认:active task、当前阶段、spec 索引、硬件锁。
2. 五问重启
读 active task 的 prd.md / research.md / edits.md 和 .auto-embedded/workflow.md 当前阶段块,回答:
- 当前在哪个 RIPER 阶段 2. 最近改了什么 3. 硬件资源现状
- 之前 RESEARCH 发现了什么 5. {{#AGENT_CAPABLE}}现在该以哪个角色(Scout/Builder/Verifier)继续{{/AGENT_CAPABLE}}{{^AGENT_CAPABLE}}下一步的最小动作是什么{{/AGENT_CAPABLE}}
3. 按阶段路由继续
- RESEARCH → 补证据 / 引脚规划
- INNOVATE → 评候选方案
- PLAN → 出/补实施清单(含
review:true项须用户确认) - EXECUTE → 按轮次实现,一轮一个改动点 + 验证证据;切阶段用
{{PYTHON_CMD}} .auto-embedded/scripts/task.py phase EXECUTE - REVIEW → 跑验证门 + 分层门禁,然后 {{CMD_REF:finish-work}}
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.
- 4d ago First seen · 22 lines · 0 tokens per session scan A a8d020bec472
continue is a command published in the GitHub repository DunCanYounG-1/auto-embedded (218 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 326 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 2026-08-30.
Other commands, from other repositories
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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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.