S
Shaisolaris/solaris-dev-shop
61 specialist workflows with executable local tools, evidence checks and an explainable task router
SECURITY.md ✓
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- Star count
- 1 ★ · Shaisolaris/solaris-dev-shop · read from the GitHub search API · (checked 2026-11-02 20:00:41)
- Source
- read directly from its GitHub page · type: open-source project
- Harvest history
- first seen 2026-10-23 · last seen 2026-11-14 · seen 26× · listed by 2 sources
- Score
- score 203 · 1 ★ · 2 sources · repo
FAQ (answers come from our records)
Who is it for?
We filed it under these tags: Agent 技能. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository
Shaisolaris/solaris-dev-shop;first catalogued 2026-10-23;last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.# Solaris Dev Shop
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
Find the right specialist skill, route a task, and carry its evidence requirements into your own agent.
61 portable specialist skills across 12 departments, plus a chief-of-staff skill and an optional deterministic Python router. Free under MIT. No model calls, account or API key is needed to try the router.
The router produces an assignment packet with one accountable lead and, when needed, multiple supporting specialists. To do the work, open those skills in your own agent or agents with the tools and permissions that task needs. The router does not start agents or grant access to your accounts.
## Native plugins
Use the native plugin repository for host-specific installation instructions, tested client versions and publication status. The packages keep the same canonical workflows and companion resources together and record their exact source revision. Native format support, model-driven results and provider-directory approval have separate evidence; check the recorded scope for your client and operating system.
## Try it
Requires Git and Python 3.10+. This first run leaves your PATH unchanged:
bash
git clone https://github.com/Shaisolaris/solaris-dev-shop.git
cd solaris-dev-shop
python3 control-plane/metacontrolplane.py skills playwright
python3 control-plane/metacontrolplane.py intake --explain "Write a test plan for the client portal login regression"
On Windows, use python in place of python3.
The intake selects solaris.qa-engineer and returns:
json
"decision": "assign",
"assignment": {
"primarycapability": "solaris.qa-engineer",
"skillpath": "employees/quality-security/qa-engineer/SKILL.md"
},
"performedwork": false
This is an excerpt; the full packet includes authority bounds, required evidence, confidence and runner-up. Confidence measures keyword evidence, not the probability that a result is correct. An unclear goal asks for clarification. Recognized high-risk wording triggers a human-review gate. Risk matching is lexical and does not grant permission for actions that are not flagged.
Next: open the returned SKILL.md in your agent, keep its companion files together, and supply the task and workspace. Follow one complete handoff, browse the 61 skills, or use the Actions playground without a local install.
Watch the 65-second narrated walkthrough · Transcript, captions and reproducible commands
## Choose a skill
After the optional ./install.sh setup, the same commands are available as solaris-intake:
bash
solaris-intake skills accessibility --department quality-security
solaris-intake skills "landing page" --json
solaris-intake intake --explain "review this code"
Search covers public names, summaries and tags. All query terms must match. Results include the source-tree path and GitHub link; searching does not install or execute a skill. The Python wheel contains the router and catalog, while the complete skill folders live in this repository.
## Work with multiple specialists
One assignment can include several specialists working toward the same outcome:
bash
python3 control-plane/metacontrolplane.py intake --explain "Build a FastAPI REST API backend; design Figma wireframes; write a Playwright test plan"
61 portable specialist skills across 12 departments, plus a chief-of-staff skill and an optional deterministic Python router. Free under MIT. No model calls, account or API key is needed to try the router.
The router produces an assignment packet with one accountable lead and, when needed, multiple supporting specialists. To do the work, open those skills in your own agent or agents with the tools and permissions that task needs. The router does not start agents or grant access to your accounts.
## Native plugins
Use the native plugin repository for host-specific installation instructions, tested client versions and publication status. The packages keep the same canonical workflows and companion resources together and record their exact source revision. Native format support, model-driven results and provider-directory approval have separate evidence; check the recorded scope for your client and operating system.
## Try it
Requires Git and Python 3.10+. This first run leaves your PATH unchanged:
bash
git clone https://github.com/Shaisolaris/solaris-dev-shop.git
cd solaris-dev-shop
python3 control-plane/metacontrolplane.py skills playwright
python3 control-plane/metacontrolplane.py intake --explain "Write a test plan for the client portal login regression"
On Windows, use python in place of python3.
The intake selects solaris.qa-engineer and returns:
json
"decision": "assign",
"assignment": {
"primarycapability": "solaris.qa-engineer",
"skillpath": "employees/quality-security/qa-engineer/SKILL.md"
},
"performedwork": false
This is an excerpt; the full packet includes authority bounds, required evidence, confidence and runner-up. Confidence measures keyword evidence, not the probability that a result is correct. An unclear goal asks for clarification. Recognized high-risk wording triggers a human-review gate. Risk matching is lexical and does not grant permission for actions that are not flagged.
Next: open the returned SKILL.md in your agent, keep its companion files together, and supply the task and workspace. Follow one complete handoff, browse the 61 skills, or use the Actions playground without a local install.
Watch the 65-second narrated walkthrough · Transcript, captions and reproducible commands
## Choose a skill
After the optional ./install.sh setup, the same commands are available as solaris-intake:
bash
solaris-intake skills accessibility --department quality-security
solaris-intake skills "landing page" --json
solaris-intake intake --explain "review this code"
Search covers public names, summaries and tags. All query terms must match. Results include the source-tree path and GitHub link; searching does not install or execute a skill. The Python wheel contains the router and catalog, while the complete skill folders live in this repository.
## Work with multiple specialists
One assignment can include several specialists working toward the same outcome:
bash
python3 control-plane/metacontrolplane.py intake --explain "Build a FastAPI REST API backend; design Figma wireframes; write a Playwright test plan"
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