dsh-thinking-language-zh
ayanJava111
deepseek harness思考过程中文插件
wellorbetter/dsh-product-delivery-workflow
100% AI-native product delivery workflow plugin for DeepSeek Harness: full product-to-release pipeline (research → PRD → OpenSpec → parallel multi-agent → review loops → tests → release audit) with loop closure. 产品交付工作流插件:从产品到发布全流程,自带闭环,100% AI 原生,睡前启动醒来收货。
PROJECT TOPICS
PROJECT README
A product delivery workflow plugin for DeepSeek Harness: a full product-to-release pipeline with loop closure, built for high-quality autonomous completion of long, hard tasks.
Kick it off before you sleep; wake up to the final report.
100% AI-native — no human in the loop: autonomous research, architecture, implementation, review, testing, and release audit, end to end.
Installing this bundle adds one workflow skill + nine role-agent skills to every session of the target dsh profile (via the model-facing skill tool and ctx.skills). No other configuration is needed.
| Skill | Role |
|---|---|
product-delivery-workflow |
The orchestrator: 10 stage gates from brief to release, artifact-driven, with review loops and a required final report. |
product-agent |
Product manager: evidence-backed decisions (BUILD / REFINE / REJECT), PRDs with acceptance criteria and metrics. |
architect-agent |
Senior architect: OpenSpec proposals, component boundaries, interfaces, contracts, and dependency-ordered task graphs. |
senior-dev-agent |
Senior developer: bounded implementation from contracts, deterministic tests, explicit error handling. |
agent-team |
Multi-agent team/swarm: bounded subagents, parallel workflows, disjoint ownership, independent review. |
perf-reviewer-agent |
Read-only performance reviewer against PRD budgets. |
test-agent |
Automated testing and manual platform/device verification against contracts and acceptance criteria. |
memory-curator |
Safe cross-session memory candidates from approved evidence only. |
evolution-agent |
Measurable workflow improvements as evidence-backed proposals. |
release-audit-agent |
Read-only pre-commit / pre-GitHub release audit (secrets, privacy, hygiene). |
Brief → Research → Product Decision → PRD → OpenSpec Architecture
→ Parallel Implementation (one bounded agent per task)
→ Independent Review Loop (correctness / architecture / performance)
→ Tests & Acceptance → Memory & Evolution → Release Audit
→ Required Final Report ──┐
└── findings route back to workers → loop until PASS
The loop is the point: every review finding routes back to the responsible worker and repeats until all reviewers pass (5 cycles max, then it asks for human direction). Nothing is claimed unless its artifact or verification result exists.
.opencode/workflow/<slug>/ (01-research.md → 10-*), so you can audit the whole run after sleeping.git commit / PR / push, and memory curation never stores secrets or transcripts.evolution-agent + memory-curator turn each run's evidence into proposals and durable memory for the next one.Requires the dsh CLI (install DeepSeek Harness).
# from GitHub (recommended)
dsh plugin --profile web add github:wellorbetter/dsh-product-delivery-workflow
# or from a local checkout
dsh plugin --profile web add ./dsh-product-delivery-workflow
Restart the profile (dsh web / dsh --profile <name>) after installing. The plugin is a bundle: it declares dsh.bundle.patch, so dsh plugin reconciles it into the profile's dsh.profile.bundles layer list automatically. It ships plain JavaScript (lib/index.js), so a GitHub install needs no build step or allowBuilds permission.
In any session of the profile, ask for the workflow — the orchestrator loads the role skills itself:
Run the product delivery workflow on
<brief>. Produce the full pipeline and the final report. You may work autonomously; loop until the gates pass.
Or invoke a single role for a bounded task:
Use product-agent to review this PRD against the delivery results and report gaps.
For overnight runs, pair it with the goal/headless mode: start a session with the brief, let it loop, and check the .opencode/workflow/<slug>/ artifacts and final report in the morning.
pnpm install
pnpm verify # discovers + loads all 10 packaged skills through the provider
MIT
CLASSIFICATION EVIDENCE
系统优先读取 GitHub Topics,再与站内分类词典和词根规则比对。