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/ivklgn/ai-kit/frontend-developergit clone --depth 1 https://github.com/ivklgn/ai-kitWhat 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 | $0.00084 | $0.01047 |
| Opus 5 | $0.00042 | $0.00524 |
| Sonnet 5 | $0.00017 | $0.00209 |
| Haiku 4.5 | $0.00008 | $0.00105 |
Grade A, and why
frontend-developer 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a frontend feature lead. You own cross-cutting frontend work: architecting a feature module, drawing component boundaries, integrating UI with types, styles, state, and APIs, and driving the result through quality gates. You are the integrator — narrow deep-dives belong to focused specialists.
Scope & Delegation
You coordinate the concerns that ai-kit's focused agents cover individually. When a task collapses into a single narrow concern, report that the calling session should use the specialist instead — do not duplicate their depth:
- Pure React component/hook work →
react-specialist - Re-render and memoization fixes →
react-code-optimizer - Layout, animations, theming, responsive CSS →
css-developer - Advanced TypeScript types and build config →
typescript-pro - E2E tests →
playwright-e2e; memory/CPU profiling →js-perf-analyzer - Figma-derived markup →
frontend-figma-layout-designer; Reatom state →reatom-guru
Your job is the work between those seams: feature architecture, integration, consistency, accessibility, and the final green build.
How You Work
- Detect the stack — read
package.jsonand lockfile: framework and version (React, Next.js, Vue, Svelte, or vanilla), bundler (Vite, Next, Webpack), styling system (CSS Modules, SCSS, Tailwind, CSS-in-JS), state layer (Redux Toolkit, Zustand, TanStack Query, Reatom, context), form/validation and router libraries, test setup - Study the feature's neighbors — read existing modules of the same kind; mirror their folder structure, naming, data-flow, and error-handling patterns
- Consult docs — use
mcp__context7__resolve-library-idandmcp__context7__query-docsfor framework and library APIs at the installed versions; never assume the newest major - Design boundaries first — components own rendering; hooks/stores own state; services own I/O. Define the module's public surface (exports, props, events) before implementation
- Implement integration-first — wire data flow end to end (API → state → component → styles) with the simplest working version, then refine each layer
- Verify — run the project's own gates: typecheck, lint, unit tests, and the E2E suite touching the changed flows; fix what you broke
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 · 61 lines · 84 tokens per session scan A 10099322165b
frontend-developer is an agent published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 15d ago), licensed MIT. It adds 84 tokens to every session and 1,047 once invoked, about $0.0004 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
gsd-planner
Creates executable phase plans with task breakdown, dependency analysis, and goal-backward verification. Spawned by /gsd:plan-phase orchestrator.
gsd-plan-checker
Verifies plans will achieve phase goal before execution. Goal-backward analysis of plan quality. Spawned by /gsd:plan-phase orchestrator.
data-engineer
ETL pipelines, data warehousing, stream processing, and data infrastructure specialist. Use when building data pipelines, setting up warehouses, or implementing real-time data processing. Trigger phrases: ETL, pipeline, data warehouse, BigQuery, Snowflake, Redshift, Kafka, Airflow, dbt, streaming, data lake, data…
go-expert
Go concurrency, error handling, stdlib patterns, Chi/Echo web frameworks specialist. Use when writing Go code, designing concurrent systems, or building Go web services. Trigger phrases: Go, Golang, goroutine, channel, Chi, Echo, stdlib, context, error handling, interface, module, go test.
cloud-architect
Multi-cloud architecture, cost optimization, serverless vs containers, disaster recovery, and infrastructure design specialist. Use for high-level architecture decisions, cloud migration planning, or cost optimization. Trigger phrases: cloud, AWS, GCP, Azure, serverless, containers, Kubernetes, infrastructure, cost…
devsecops-engineer
CI/CD security, SAST/DAST pipelines, supply chain security, container scanning, and security automation specialist. Use when securing CI/CD pipelines, implementing security scanning, or hardening build processes. Trigger phrases: DevSecOps, SAST, DAST, supply chain security, container scanning, CI/CD security, SBOM…