Optimize detection thresholds per transaction type, reduce false positives, tune velocity windows, calibrate ML model, improve graph analysis depth
Optimize detection thresholds per transaction type, reduce false positives, tune velocity windows, calibrate ML model, improve graph analysis depth
- Primitives
- 10
- WAF pillars
- 5
- Manifest
- yes
- Root agent
- yes
DevKit
10 primitives across 4 types
The authoring surface — every primitive this play composes from. Primitives live under .github/ in the source repo and are loaded by the FAI Engine according to the manifest.
agents
3Reasoning + tool-calling entities. Each agent declares its model, system prompt, and the skills/tools it composes.
skills
3Reusable, multi-step capability definitions. A skill is a folder containing a SKILL.md describing how to compose lower-level primitives.
instructions
3Behavioural rules scoped by `applyTo` globs. Loaded into every agent that matches the scope.
hooks
1Event-driven scripts triggered by lifecycle events (SessionStart, AfterAgentInvoke, OnGuardrailViolation, …).
Why this matters: A play's DevKit is the answer to “what does this system do?” SpecKit (next tab) is the answer to “how is it wired?” — read them together for the full picture.
Deploy this play
Opens portal.azure.com pre-loaded with this play's Bicep. Nothing provisions until you confirm there.
Open this play
Open in VS Code
Desktop · clones the FrootAI repo
Open in vscode.dev
Browser · no install needed · always works
Open in Cursor
Desktop · cursor:// URI scheme
Copy clone command
git clone https://github.com/frootai/frootai.git && cd frootai/frootai/plays
View on GitHub
Browse the play source in your browser
Desktop schemes (vscode://, cursor://) require the app installed. The vscode.dev link always works in the browser.
📰 The Friday Letter
Weekly: this week's release, 1 community highlight, 1 play spotlight, 1 useful link. 600–1,000 words. No filler.