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.
git clone --depth 1 https://github.com/dhslegen/digital-delivery-teamWrote 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/dhslegen/digital-delivery-team/kickoff)<a href="https://agentmods.dev/commands/dhslegen/digital-delivery-team/kickoff"><img src="https://agentmods.dev/badge/commands/dhslegen/digital-delivery-team/kickoff/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/dhslegen/digital-delivery-team/kickoff"><img src="https://agentmods.dev/badge/commands/dhslegen/digital-delivery-team/kickoff.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 | $0.00037 | $0.01083 |
| Opus 5.5 | $0.00015 | $0.00433 |
| Sonnet 5.5 | $0.00007 | $0.00217 |
| Haiku 4.5 | $0.00004 | $0.00108 |
Grade A, and why
kickoff scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/kickoff
输入:$ARGUMENTS(补充需求描述,透传给 /prd)
执行步骤
Step 0:技术栈预选(M6.3 新增)
LLM 必须执行:在跑 /prd 之前,先检查 project-brief.md 中的 "技术栈预设" 字段。
| 字段值 | 行为 |
|---|---|
具体 preset(java-modern / node-modern ...) |
跳过问卷,按 preset 解析 |
interactive 或缺失 |
必须用 AskUserQuestion 工具发起 4 步问卷(Spring Initializr 等价:语言 → 数据库 → 前端 → UI) |
custom 且 brief 已填详细字段 |
按详细字段解析,不再问 |
custom 但 brief 字段不全 |
用 AskUserQuestion 补全缺失字段 |
具体 4 步问卷模板见 commands/design.md::Phase 2b,或直接读取 $DDT_PLUGIN_ROOT/templates/tech-stack-options.yaml::askuserquestion_flow(插件根——v0.9.3 D19)。
收集到答案后,把结果写入 .ddt/components.json.tmp(项目本地路径,多项目并行不冲突,跑完即删),必须使用嵌套对象 schema:
{
"preset": "<step1 推断的 preset 名>",
"backend": { "language": "...", "framework": "...", "database": { "primary": "..." } },
"frontend": { "framework": "...", "ui": { "components": "..." } },
"ai_design": { "type": "claude-design | figma | v0" }
}
严禁写成扁平字符串(如 "backend": "java-spring-boot")—— resolve-tech-stack.mjs 会拒绝并退出 2,污染源默认 preset 的字段。后续 /design 阶段会 merge。
M6.2 执行模式
- 默认 interactive 模式:每个内部 phase(prd / wbs / design)跑完后必须暂停走决策门(
skills/decision-gate/SKILL.md),未确认前禁止进入下一步 - --auto 模式:传
--auto时跳过所有决策门,按旧串行 chain 跑(兼容 v0.5.x 老用户的"一键起手"体验)
Step 1:跑 /prd $ARGUMENTS
- 若
project-brief.md缺失 → 停止,提示用户填写 - 若存在阻塞项(
docs/blockers.md非空)→ 停止,提示处理阻塞 - /prd 命令内部已含决策门(除非 --auto);用户接受后再继续 Step 2
- 未传 --auto 时:LLM 必须等待 /prd 决策门返回
accept后才推进到 /wbs
Step 2:跑 /wbs
- 若失败 → 停止
- /wbs 内部决策门同上
- 未传 --auto 时:LLM 必须等待 /wbs 决策门返回
accept后才推进到 /design
Step 3:跑 /design $ARGUMENTS(透传 --preset / --ai-design)
- /design 内部 Phase 2b 会基于 Step 0 收集的 components JSON 写入
.ddt/tech-stack.json - 若契约 lint 未通过 → 停止,返回退出码 4
- 若 OpenAPI lint 工具缺失 → 停止,返回退出码 5
- 若产出文件缺失 → 停止
- /design 内部决策门同上
- 未传 --auto 时:LLM 必须等待 /design 决策门返回
accept后才输出 kickoff 汇总
- 汇总输出:
/kickoff 完成
PRD 用户故事数: <n> 条
WBS 任务数: <n> 个
Endpoint 数: <n> 个
Top 3 风险:
1. <risk-1>
2. <risk-2>
3. <risk-3>
建议下一步:/impl
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.
- 1mo ago First seen · 81 lines · 37 tokens per session scan A 5243b4b39406
kickoff is a command published in the GitHub repository dhslegen/digital-delivery-team (1 stars, last pushed 5mo ago), licensed MIT. It adds 37 tokens to every session and 1,083 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 2026-08-31.
Other commands, from other repositories
scout-meta-review
Run an interactive Scout meta-review — a system-level audit that sits above the individual session types. Checks whether sessions are running, mistake audit is trending well, proposals are flowing, KB files are healthy, and data-source coverage is consistent across session types. Runs in the current conversation.
scout-work
Interactive work session — walks through today's actionable items one at a time, presents a recommended action with draft content, and executes each one only with explicit approval. Runs in the current conversation (not as a background session).
execute
Execute the next available tracked task with TDD, pre-commit validation, PR creation, AI code review, and issue tracker bridge sync.
dashboard
Compact visual progress dashboard with progress bar, task table, dependency graph, and active/blocked/next status.
sync
Reconcile coco tracker state with the configured issue tracker. Syncs task statuses and reports mismatches.
planning-triage
Quick-score an enhancement, bug, or feedback item using the impact-first triage framework. Creates an issue if approved.