team-dora

team-dora is a skill for Claude Code from ketor/cto-fleet. It costs 141 tokens per session (8,256 once invoked), scanned B, original, Apache-2.0.

A DORA metrics reporting workflow that uses version-control and CI data to assess how a software team delivers and recovers from changes. DORA metrics cover deployment frequency, delivery lead time, change failure rate, and recovery time.

In plain words
What is it for?
Use it to collect data for periods from one week to three months, compare with the previous period, and produce improvement suggestions and trend reports.
Why use it?
It turns scattered development and delivery data into a consistent view of engineering performance and areas needing improvement.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: reads .claude/ paths; names the AskUserQuestion tool.

Good fit Use it to collect data for periods from one week to three months, compare with the previous period, and produce improvement suggestions and trend reports.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ketor/cto-fleet/team-dora
Install

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.

Any agent
npx skills add ketor/cto-fleet --skill team-dora
Clone the repo
git clone --depth 1 https://github.com/ketor/cto-fleet

Made for: Claude Code.

Wrote 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.

agentmods badge for team-dora

README.md
[![agentmods](https://agentmods.dev/badge/skills/ketor/cto-fleet/team-dora.svg)](https://agentmods.dev/skills/ketor/cto-fleet/team-dora)
Your own site
<a href="https://agentmods.dev/skills/ketor/cto-fleet/team-dora"><img src="https://agentmods.dev/badge/skills/ketor/cto-fleet/team-dora.svg" alt="Measured on agentmods" height="20"></a>
Per session 141 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,256 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00141 $0.08256
Opus 5 $0.00071 $0.04128
Sonnet 5 $0.00028 $0.01651
Haiku 4.5 $0.00014 $0.00826

Measured 8d ago against content hash 100fc0b5ec07, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade B, and why

team-dora scanned grade B with 1 finding 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 8d 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.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

- 目录路径:`/tmp/{team-name}/`(team lead 在 TeamCreate 后执行 `mkdir -p /tmp/{team-name} && chmod 700 /tmp/{team-name}`)
team-dora/SKILL.md · 611 lines

How it starts

The opening of the file, as written. The whole thing — 611 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Preamble (run first)

_UPD=$(~/.claude/skills/cto-fleet/bin/cto-fleet-update-check 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD" || true

If output shows UPGRADE_AVAILABLE <old> <new>: read ~/.claude/skills/cto-fleet/cto-fleet-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined). If JUST_UPGRADED <from> <to>: tell user "Running cto-fleet v{to} (just updated!)" and continue.

参数解析:从 $ARGUMENTS 中检测以下标志:

  • --auto:完全自主模式(不询问用户任何问题,全程自动决策)
  • --once:单轮确认模式(将所有需要确认的问题合并为一轮提问,确认后全程自动执行)
  • --period=1w|2w|1m|3m:分析周期(可选,默认 2w,即两周)
  • --compare:与上一周期对比(可选,启用后输出趋势变化)
  • --lang=zh|en:输出语言(默认 zh 中文)

解析后将标志从分析需求描述中移除。

模式 用户确认范围 条件节点处理
标准模式(默认) 数据源确认 + 最终报告确认 正常询问用户
单轮确认模式--once 仅最终报告确认 自动决策 + 收尾汇总
完全自主模式--auto 不询问用户 全部自动决策,收尾汇总所有决策

单轮确认模式下自动决策规则:

  • 数据源不完整(缺少 CI/CD 数据) → collector 标注"该数据源不可用,基于 git 推断",不阻塞流程
  • 两位 analyzer 对同一指标的评级差异过大(相差 2 级及以上)不可跳过,必须暂停问用户(熔断机制)
  • 发现 DORA 指标全部处于 Low 水平不可跳过,必须暂停问用户(熔断机制)
  • git 历史不足以覆盖指定周期 → collector 标注"数据不足,实际分析周期为 X",不阻塞流程
  • 发现异常数据点(如单次提交含 1000+ 文件变更) → analyzer 自行判断是否过滤

完全自主模式下:所有节点均自动决策,不询问用户。熔断机制仍然生效(评级差异过大、全部 Low 水平时仍必须暂停问用户)。

使用 TeamCreate 创建 team(名称格式 team-dora-{YYYYMMDD-HHmmss},如 team-dora-20260308-143022,避免多次调用冲突),你作为 team lead 按以下流程协调。

文件交接规范(File-Based Handoff)

所有 agent 间传递详细报告时,必须采用文件交接模式(防止上下文溢出触发 20MB 限制):

  1. 写入文件:将完整报告写入团队工作目录:
    • 目录路径:/tmp/{team-name}/(team lead 在 TeamCreate 后执行 mkdir -p /tmp/{team-name} && chmod 700 /tmp/{team-name}
    • 单个文件 ≤ 2000 行;超大报告拆分为 summary + details 文件
  2. 发送引用:通过 SendMessage 仅发送(≤500 字符):
    • 文件路径(1 行)
    • 关键摘要(含核心指标/发现/评分)
  3. 按需读取:接收方使用 Read 按需读取文件,发送方不内联完整内容
  4. 路径转发:team lead 转发报告时只转发文件路径 + 摘要,不 Read 后再 SendMessage
  5. 遵从校验:team lead 收到超 1000 字符且不含 /tmp/team- 路径前缀的消息时,要求 agent 以文件交接模式重发

Read the full file on GitHub · 611 lines

Changes

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.

  1. 8d ago First seen · 611 lines · 0 tokens per session scan B 100fc0b5ec07

Subscribe to this mod's changes

team-dora is a skill published in the GitHub repository ketor/cto-fleet (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 141 tokens to every session and 8,256 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

prowler-commit

Creates professional git commits following conventional-commits format. Trigger: When creating commits, after completing code changes, when user asks to commit.

prowler-cloud/prowler · 33 tokens

gh-auth-isolation

Safely manage multiple GitHub identities (EMU + personal) in agent workflows.

github/gh-aw · 20 tokens

comet-github

A routing guide for Comet-related GitHub work. It directs requests about pull requests, issues, CI failures, ideas, and fixes to the appropriate review or implementation process.

rpamis/comet · 72 tokens

github-skill

Work with GitHub via the gh CLI — clone repositories, create/list/merge pull requests, create/list issues, and run any other gh command (API calls, workflow runs, releases, repo administration). List operations return parsed JSON.

zeenie-ai/OpenCompany · 51 tokens

codex-autoresearch

Run autonomous, measurable experiments in a Git repository: change one hypothesis, verify a numeric metric, keep improvements, and revert failures. Use when the user wants Codex to keep iterating toward a numeric target in the foreground or as a detached background run. Do not use for ordinary one-shot coding…

leo-lilinxiao/codex-autoresearch · 80 tokens

changelog-composer

Generates structured changelogs and release notes from git history and PRs, classifying breaking changes, features, fixes, performance, docs. Triggers on: "generate changelog", "write release notes", "what changed since", "prepare release", "release notes for", "diff since tag".

Mathews-Tom/armory · 67 tokens