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disintodisinto 开发

Agent Skill

disinto 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 OpenClaw 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

总安装

3,420

周安装

137

GitHub Stars

公开资料未说明

下载量

1,107
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:disinto(disinto 开发)
来源仓库:https://github.com/johba37/disinto
安装命令:
openclaw skills install disinto
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install disinto

简介

管理 disinto 自主代码工厂的运营流程。

  • 支持提交 Issue、阅读代理日志与检查 CI 状态。
  • 适用于团队协作与自动化流水线维护。disinto 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 需 GitHub 仓库写入权限以操作 Issue 与 PR。
  • 建议定期审计日志与 CI 运行结果。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

SKILL.md

name
disinto
description
>-
license
AGPL-3.0
metadata
author
johba
version
0.1.1
env_vars
required
optional
tools

Disinto Factory Skill

Disinto is an autonomous code factory with nine agents that implement issues, review PRs, plan from a vision, predict risks, groom the backlog, gate actions, and assist the founder — all driven by cron and Claude.

Required environment

VariablePurpose
FORGE_TOKENForgejo/Gitea API token with repo scope
FORGE_APIBase API URL, e.g. https://forge.example/api/v1/repos/owner/repo
PROJECT_REPO_ROOTAbsolute path to the checked-out disinto repository

Optional:

VariablePurpose
WOODPECKER_SERVERWoodpecker CI base URL (for pipeline queries)
WOODPECKER_TOKENWoodpecker API bearer token
WOODPECKER_REPO_IDNumeric repo ID in Woodpecker

The nine agents

AgentRoleRuns via
DevPicks backlog issues, implements in worktrees, opens PRsdev/dev-poll.sh (cron)
ReviewReviews PRs against conventions, approves or requests changesreview/review-poll.sh (cron)
GardenerGrooms backlog: dedup, quality gates, dust bundling, stale cleanupgardener/gardener-run.sh (cron 0,6,12,18 UTC)
PlannerTracks vision progress, maintains prerequisite tree, files constraint issuesplanner/planner-run.sh (cron daily 07:00 UTC)
PredictorChallenges claims, detects structural risks, files predictionspredictor/predictor-run.sh (cron daily 06:00 UTC)
SupervisorMonitors health (RAM, disk, CI, agents), auto-fixes, escalatessupervisor/supervisor-run.sh (cron */20)
ActionExecutes operational tasks dispatched by planner via formulasaction/action-poll.sh (cron)
VaultGates dangerous actions, manages resource procurementvault/vault-poll.sh (cron)
ExecInteractive executive assistant reachable via Matrixexec/exec-session.sh

How agents interact

Planner ──creates-issues──▶ Backlog ◀──grooms── Gardener
   │                           │
   │                           ▼
   │                     Dev (implements)
   │                           │
   │                           ▼
   │                     Review (approves/rejects)
   │                           │
   │                           ▼
   ▼                        Merged
Predictor ──challenges──▶ Planner (triages predictions)
Supervisor ──monitors──▶ All agents (health, escalation)
Vault ──gates──▶ Action, Dev (dangerous operations)
Exec ──delegates──▶ Issues (never writes code directly)

Issue lifecycle

backlogin-progress → PR → CI → review → merge → closed.

Key labels: backlog, priority, in-progress, blocked, underspecified, tech-debt, vision, action, prediction/unreviewed.

Issues declare dependencies in a ## Dependencies section listing #N references. Dev-poll only picks issues whose dependencies are all closed.

Available scripts

  • scripts/factory-status.sh — Show agent status, open issues, and CI

pipeline state. Pass --agents, --issues, or --ci for specific sections.

  • scripts/file-issue.sh — Create an issue on the forge with proper labels

and formatting. Pass --title, --body, and optionally --labels.

  • scripts/read-journal.sh — Read agent journal entries. Pass agent name

(planner, supervisor, exec) and optional --date YYYY-MM-DD.

Common workflows

1. Check factory health

bash scripts/factory-status.sh

This shows: which agents are active, recent open issues, and CI pipeline status. Use --agents for just the agent status section.

2. Read what the planner decided today

bash scripts/read-journal.sh planner

Returns today's planner journal: predictions triaged, prerequisite tree updates, top constraints, issues created, and observations.

3. File a new issue

bash scripts/file-issue.sh --title "fix: broken auth flow" \
  --body "$(cat scripts/../templates/issue-template.md)" \
  --labels backlog

Or generate the body inline — the template shows the expected format with acceptance criteria and affected files sections.

4. Check the dependency graph

python3 "${PROJECT_REPO_ROOT}/lib/build-graph.py" \
  --project-root "${PROJECT_REPO_ROOT}" \
  --output /tmp/graph-report.json
cat /tmp/graph-report.json | jq '.analyses'

The graph builder parses VISION.md, the prerequisite tree, formulas, and open issues. It detects: orphan issues (not referenced), dependency cycles, disconnected clusters, bottleneck nodes, and thin objectives.

5. Query a specific CI pipeline

bash scripts/factory-status.sh --ci

Or query Woodpecker directly:

curl -s -H "Authorization: Bearer ${WOODPECKER_TOKEN}" \
  "${WOODPECKER_SERVER}/api/repos/${WOODPECKER_REPO_ID}/pipelines?per_page=5" \
  | jq '.[] | {number, status, commit: .commit[:8], branch}'

6. Read and interpret VISION.md progress

Read VISION.md at the repo root for the full vision. Then cross-reference with the prerequisite tree:

cat "${PROJECT_REPO_ROOT}/planner/prerequisite-tree.md"

The prerequisite tree maps vision objectives to concrete issues. Items marked [x] are complete; items marked [ ] show what blocks progress. The planner updates this daily.

Gotchas

  • Single-threaded pipeline: only one issue is in-progress per project at a

time. Don't file issues expecting parallel work.

  • Secrets via env vars only: never embed secrets in issue bodies, PR

descriptions, or comments. Use $VAR_NAME references.

  • Formulas are not skills: formulas in formulas/ are TOML issue templates

for multi-step agent tasks. Skills teach assistants; formulas drive agents.

  • Predictor journals: the predictor does not write journal files. Its memory

lives in prediction/unreviewed and prediction/actioned issues.

  • State files: agent activity is tracked via state/.{agent}-active files.

These are presence files, not logs.

  • ShellCheck required: all .sh files must pass ShellCheck. CI enforces this.

适合场景

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用户想查找某类 Agent Skill 时

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能力概览

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

81.34%
按下载量换算900

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

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安装前确认

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