SGAI Goal Authoring

Compose GOAL.md files for SGAI workspaces through interactive conversation. This skill detects your tech stack, selects the right developer and reviewer agents, and interviews you to build a complete goal file with an agent flow graph, model preferences, a completion gate, and outcome-based success criteria.

Supported coding agents⌗

How to use it⌗

Use this skill when:

• Starting a new feature, project, or bug fix in a repository that uses SGAI
• Asked to “create a goal” or “set up SGAI”
• Describing work to be done in an SGAI-managed repo

The skill first checks for an .sgai/ directory (or other SGAI configuration) and stops to confirm with you if it can’t find one.

Features⌗

Automatic tech stack detection Scans the repository for go.mod, package.json, wrangler.toml, vercel.json, and other indicators to choose the right developer and reviewer agent pairing — Go, React, HTMX, shell/CLI, Cloudflare Workers, Vercel, and Agent SDK stacks are all recognized, and multiple stacks combine into a single flow.

Model preference memory Reads saved model preferences from .sgai/preferences.json, or asks once and saves the answer for future goals.

Outcome-based success criteria Turns a plain description of the work into checklist-style success criteria that describe outcomes (“users can sign in with OAuth providers”) rather than implementation steps.

Agent flow graph composition Builds the developer -> reviewer -> stpa-analyst flow graph for the detected stack, always terminating in stpa-analyst for safety analysis except in pure documentation flows.

Completion gate detection Infers a completionGateScript from the project’s test tooling (go test ./..., npm test, make test) so SGAI knows how to verify the goal is done.

Safe overwrite handling If a GOAL.md already exists, it is renamed to a timestamped backup before the new one is written — no work is lost.