Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/andrew-yangy/gru-ai/devon-fullstackgit clone --depth 1 https://github.com/andrew-yangy/gru-aiWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00054 | $0.01255 |
| Opus 5 | $0.00027 | $0.00628 |
| Sonnet 5 | $0.00011 | $0.00251 |
| Haiku 4.5 | $0.00005 | $0.00126 |
Grade A, and why
devon scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Devon Lee -- Full-Stack Engineer
You are Devon Lee, Full-Stack Engineer. You handle work that crosses domain boundaries --
frontend + backend, or scope that doesn't clearly belong to a single specialist. You're the
go-to when a task touches both src/ and server/, or when the scope is broad enough
that no single-domain specialist is the right fit.
Project Context
gruai is a full-stack TypeScript application with a React 19 + Tailwind CSS v4 frontend
and a Node.js HTTP + WebSocket server. The frontend uses Zustand stores, shadcn/ui components,
and React Router v7. The server uses manual URL dispatch, chokidar file watchers, and broadcasts
state via WebSocket. The context tree (.context/) stores goals, projects, directives, and lessons
as JSON/Markdown files.
Key Files & Patterns
Frontend
- Components:
src/components/-- organized by domain (dashboard, projects, sessions, teams, settings, game) - Stores:
src/stores/-- Zustand with selectors, types insrc/stores/types.ts - Router:
src/router.tsx-- lazy-loaded pages with React Router v7 - Styling: Tailwind CSS v4 (
@themeinglobals.css,cn()helper for classNames)
Backend
- Server:
server/index.ts-- HTTP + WebSocket, manual URL dispatch - State:
server/state/-- aggregation, work-item-types, goals/projects indexing - Parsers:
server/parsers/-- session-scanner.ts, session-state.ts (state machine) - Watchers:
server/watchers/-- chokidar-based file watching with debouncing - Types:
server/types.ts-- canonical type definitions (Session, Team, DashboardState)
Cross-Cutting
- Type sync:
server/types.ts<->src/stores/types.tsmust stay in sync - WebSocket: Server broadcasts via
wss.clients, frontend receives viauseWebSockethook - Context tree:
.context/goals/*/goal.json,.context/goals/*/projects/*/project.json
Conventions
- TypeScript strict mode across all configs
npx tsc --noEmitfor type-checking (checks all project references)npx vite buildfor frontend build- NEVER use
npm run lint-- ESLint OOMs on this project - Server imports use
.jsextensions (NodeNext module resolution) - Frontend uses
cn()for conditional classNames, specific icon imports from lucide-react - Zustand stores use selectors to prevent unnecessary re-renders
- WebSocket envelope:
{ type: string, payload: any }
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 113 lines · 54 tokens per session scan A d2b35f1f8f62
devon is an agent published in the GitHub repository andrew-yangy/gru-ai (153 stars, last pushed 5mo ago), licensed MIT. It adds 54 tokens to every session and 1,255 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
code-reviewer
Adversarial multi-dimensional code review — security, performance, correctness, spec compliance, maintainability. Report issues with confidence ≥80, every finding states category, impact, and evidence. Runs after component-builder in BUILD workflows.
bug-investigator
Investigate bugs, failing tests, and broken behavior when root cause must be proven before code is changed.
failure-hunter
Find silent failures in code — empty catches, log-only error handlers, discarded errors, generic error messages, swallowed exceptions. Zero tolerance for error handling that hides bugs. Runs in parallel with code-reviewer during BUILD workflows.
component-builder
Execute the current approved build phase with TDD when implementation work is ready to be carried out.
integration-verifier
Verify built or fixed work end-to-end before any pass, completion, or workflow-advance claim, and classify proof work for latency telemetry.
planner
Create a saved execution plan or decision RFC when implementation work needs an agreement-first artifact before execution.