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Agent Skill · 研究检索

agentic-backlog-scrum(Agent 积压 scrum)

agentic-backlog-scrum 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

agentic-backlog-scrum 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 72,083。

总安装 190周安装 8GitHub Stars 公开资料未说明下载 67核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agentic-backlog-scrum(Agent 积压 scrum)
来源仓库:https://github.com/hakenshi/agentic-backlog-skill
仓库路径:skills/agentic-backlog-scrum
安装命令:
npx skills add https://github.com/hakenshi/agentic-backlog-skill --skill agentic-backlog-scrum
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/hakenshi/agentic-backlog-skill --skill agentic-backlog-scrum

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

agentic-backlog-scrum 定义任务跟踪的工作流与工具使用规范。适合实施开发中的任务管理与状态同步。假设本地 agentic-backlog MCP 服务已运行。

安装命令:npx skills add https://github.com/hakenshi/agentic-backlog-skill --skill agentic-backlog-scrum。需确保后端 API 可用,否则无法读取或写入任务状态。

来源仓库内路径:skills/agentic-backlog-scrum

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/hakenshi/agentic-backlog-skill --skill agentic…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agentic-backlog-scrum 怎么安装?

在终端执行 npx skills add https://github.com/hakenshi/agentic-backlog-skill --skill agentic-backlog-s…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agentic-backlog-scrum 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agentic-backlog-scrum 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

agentic-backlog-scrum 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

agentic-backlog-scrum 用的人多吗?

公开数据是累计安装 190 次,近一周安装 8 次,下载 67 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agentic-backlog-scrum 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
agentic-backlog-scrum

Agent 积压 scrum · 本页

190—调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Agentic Backlog Scrum

Use this skill whenever you are doing implementation work and need task tracking discipline.

What this skill is

  • This skill is documentation for agent behavior.
  • It defines workflow, guardrails, and tool usage conventions.
  • It is not a database, API server, or business-logic runtime.

This skill assumes a local MCP server named agentic-backlog is available.

Runtime boundary

  • The running backlog API/application is the source of truth.
  • MCP is how the agent reads context from and sends operations to that running API.
  • This skill only tells the agent how to behave when using MCP tools.

API bootstrap fallback (required)

If backlog MCP calls fail because the API is not reachable (connection refused, timeout, 5xx from missing service), the agent must bootstrap the API container before continuing.

  1. Pull latest API image:

- docker pull lonelyww/agentic-backlog-elysia:latest

  1. Replace any stale container instance:

- docker rm -f agentic-backlog-api || true

  1. Run API on localhost :38117:

- docker run -d --name agentic-backlog-api -p 38117:8000 -e PORT=8000 -e BACKLOG_DB_PATH=/data/backlog.sqlite -v agentic-backlog-data:/data lonelyww/agentic-backlog-elysia:latest

  1. Verify health:

- curl http://127.0.0.1:38117/api/health

  1. Retry the failed backlog MCP call.

Notes:

  • Use Docker named volume agentic-backlog-data to persist SQLite without host bind mount paths.
  • If MCP points to a different port, update BACKLOG_API_BASE_URL to match (recommended default: http://127.0.0.1:38117/api).

MCP connectivity check (required)

After API bootstrap, validate MCP end-to-end before doing backlog operations:

  1. Confirm API health endpoint:

- curl http://127.0.0.1:38117/api/health

  1. Run a lightweight MCP tool call to verify data path:

- backlog.health then backlog.version - backlog.identify_project

If the MCP tool call fails because the MCP server is not configured in the current client:

  • Register a local MCP server named agentic-backlog in the active client.
  • Use local command: npx -y @hakenshi/agentic-backlog-mcp-server.
  • Set env: BACKLOG_API_BASE_URL=http://127.0.0.1:38117/api.

If the API health check fails, run the API bootstrap fallback section above.

Client examples (optional):

  • OpenCode: opencode mcp add and opencode mcp list
  • Any MCP-capable client: add server agentic-backlog with the same command/env above

Trigger phrases

Use this skill proactively when the user says things like:

  • \agentic-backlog:add
  • \agentic-backlog:remove
  • \agentic-backlog:update
  • \agentic-backlog:read
  • \agentic-backlog:board
  • \agentic-backlog:in-progress
  • \agentic-backlog:show-task
  • \agentic-backlog:update-task

Expected behavior by trigger:

  • \agentic-backlog:add -> create a task (backlog.create_task)
  • \agentic-backlog:remove -> delete only with explicit confirmation (backlog.delete_task + confirm: "DELETE")
  • \agentic-backlog:update -> update task fields or status (backlog.update_task / backlog.update_task_status)
  • \agentic-backlog:read -> fetch board/task snapshot (backlog.get_board / backlog.get_console_table)
  • \agentic-backlog:board -> return board overview (backlog.get_board + backlog.get_console_table)
  • \agentic-backlog:in-progress -> list active WIP (backlog.list_tasks with status: in_progress)
  • \agentic-backlog:show-task -> find a specific task by title keywords, then show it (backlog.find_tasks_by_title + backlog.get_task)
  • \agentic-backlog:update-task -> find a specific task by title keywords, then update it (backlog.update_task_by_title)

Task-by-name behavior:

  • Use user-provided title keywords to search current project tasks.
  • Prefer exact title match; otherwise use best partial match.
  • If multiple close matches exist, show top candidates and ask which one to use.
  • For updates, always echo the matched task title/id before applying the change.

Core tools (CRUD)

  • backlog.create_task
  • backlog.get_task
  • backlog.list_tasks
  • backlog.find_tasks_by_title
  • backlog.update_task
  • backlog.update_task_by_title
  • backlog.delete_task

Core tools (operational)

  • backlog.health
  • backlog.version

When available in current MCP version:

  • backlog.get_focus
  • backlog.claim_task
  • backlog.release_task
  • backlog.restore_task

Capability check (required)

  • Before relying on operational tools, verify availability in the current MCP server.
  • If backlog.health/backlog.version are unavailable, fallback to backlog.identify_project as connectivity check.
  • If backlog.get_focus is unavailable, fallback to backlog.get_board + backlog.list_tasks(status=in_progress|blocked).
  • If backlog.restore_task is unavailable, communicate that restore is not exposed in this MCP version.

Goal

Keep a shared backlog that multiple AI agents can update consistently.

Mandatory workflow

  1. Identify project

- Call backlog.identify_project first. - Store returned project.id.

  1. Get current board

- Call backlog.get_board and inspect WIP. - Call backlog.get_focus to prioritize blocked/stale/high-impact work. - Refresh board before each major implementation step. - When reporting progress to the user, call backlog.get_console_table.

  1. Ensure active task exists

- If no suitable task exists, call backlog.create_task.

  1. Start work

- Move task to in_progress with backlog.update_task_status or backlog.update_task.

  1. During work

- Add short progress notes with backlog.add_task_note using 3 fields: - feito: - bloqueio: - proximo: - Re-read the board after each note/status transition.

  1. On completion

- Before moving to review or done, add a compact summary note with outcome + remaining risks. - Move to review or done.

  1. On blockers

- Move to blocked and include reason.

Status model

  • backlog
  • todo
  • in_progress
  • blocked
  • review
  • done
  • cancelled

Tool usage contract

Always include metadata when available:

  • source: agent/client name (for example codex, claude-code, opencode, cursor)
  • agent_id: stable agent identity when available
  • session_id: current conversation/session id when available

Ambiguity protocol (required)

  • If a title query returns multiple plausible tasks, do not auto-apply update/delete.
  • Show top 3 candidates (id, title, status, updated_at) and request explicit selection.
  • Only proceed after user chooses one candidate.

Failure protocol (required)

  • If MCP/API is unavailable, return this standard message:

- Backlog indisponivel no momento. Vou restabelecer conexao e tentar novamente.

  • MCP fail-fast behavior:

- The MCP may open a short circuit window after timeout/5xx errors and return immediate 503 responses. - This is expected and prevents long agent stalls when API is down. - During this window, use backlog.health and backlog.version as recovery probes.

  • Then execute recovery in order:

1. backlog.health 2. API bootstrap fallback (section above) 3. backlog.version 4. Retry original operation once

  • Retry rules:

- Retry only timeout/5xx. - Do not retry 4xx validation/auth/conflict errors.

Planning mode

Use backlog.plan_from_context for fast task drafting from plain text.

  • Default behavior is preview mode.
  • Use apply=true to persist generated actions.
  • Apply only if actions are relevant to the current project scope.

Guardrails

  • Do not perform large code changes without linking to a task.
  • Keep notes objective and short.
  • Prefer one active in_progress task per agent/session.
  • Deletions must be explicit: call backlog.delete_task with confirm: "DELETE".
  • Keep updates frequent: at least one status or note update per completed sub-step.

平台分布

Codex

32.35%
按下载量换算22

Claude

29.67%
按下载量换算20

Cursor

19.08%
按下载量换算13

Gemini CLI

9.73%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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