gj-solution-plan

Draft technical solution plans from confirmed GitLab requirements. Use when a requirement needs impact analysis, architecture options, interface/data/permission changes, risk assessment, test scope, release notes, rollback notes, and Tech Lead review output.

thelastmagician/gj-gitlab-ai-workflow1 installsMITSynced Aug 27

Works with

Claude CodeCursorCodex CLIGitHub CopilotGemini CLI
---
name: gj-solution-plan
description: Draft technical solution plans from confirmed GitLab requirements. Use when a requirement needs impact analysis, architecture options, interface/data/permission changes, risk assessment, test scope, release notes, rollback notes, and Tech Lead review output.
license: MIT
---

# GJ Solution Plan

## Workflow

1. Read the confirmed requirement, acceptance criteria, linked project issue, and milestone.
2. Load minimal context from `.ai/context-index.yml`, `docs/context`, relevant `docs/modules`, and active ADRs.
3. Identify impacted modules, files, interfaces, data, permissions, operations, and rollout paths.
4. Present the recommended solution and rejected alternatives.
5. Check documentation impact:
   - Create or update `docs/technical/solutions/<feature>.md` when architecture,
     interface, data, permission, compatibility, rollout, or rollback decisions
     become durable.
   - Update `docs/modules/*.md` when module behavior or boundaries change.
   - Propose ADR updates when the decision is cross-module or long-lived.
6. List risks, owner ack needs, test scope, rollout, and rollback.
7. Write a GitLab-ready solution Issue or comment for Tech Lead review.

## Output

```markdown
## Solution Plan

Requirement:

Recommended solution:

Alternatives considered:

Impact scope:

Interface / data / permission changes:

Documentation impact:

Implementation notes:

Test scope:

Release and rollback:

Risks and owner ack:

Tech Lead review checklist:
```

## References

Read `references/demo-run.md` for the order approval solution example.

More Deployment & CI/CD skills

finetuning

microsoft/azure-skills

Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

323.2k

prisma-compute

prisma/skills

Prisma Compute deployment and hosting guide. Use whenever the user mentions Prisma Compute, `prisma.compute.ts`, `defineComputeConfig`, deploying or hosting a Prisma app, `@prisma/cli app deploy`, `compute:deploy`, `create-prisma --deploy`, `PRISMA_SERVICE_TOKEN`, Compute auth/workspaces, apps/deployments/build logs/domains, localhost vs `0.0.0.0`, deploy port binding, or framework deploy readiness for Hono, Elysia, Next.js, TanStack Start, Astro, Nuxt, Svelte, Nest, Turborepo, or custom/prebuilt artifacts.

231.4k

azure-quotas

microsoft/azure-skills

Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: \"check quotas\", \"service limits\", \"current usage\", \"request quota increase\", \"quota exceeded\", \"validate capacity\", \"regional availability\", \"provisioning limits\", \"vCPU limit\", \"how many vCPUs available in my subscription\".

187.6k

← All Deployment & CI/CD skills

Check your AI visibility

One URL in, a 0–100 score and the exact fixes out.

RUN THE CHECK

Browse all the tools

15 tools across six categories
13 of them never send your data anywhere

Free · No signup · No trial clock

SEE THE DIRECTORY