agentleFS
BuilderIOBuilderIO/agent-native/.agents/skills/workspace-conventions/SKILL.md

workspace-conventions

Skill7.6k starsChanged 5 months agoMITView on GitHub

Shared conventions for a multi-app Agent-Native workspace: finding version-matched framework docs and source, shared vs app-owned code, file and blob storage, env and secrets, agent scratch files, and Dispatch Resources. Use when working across workspace apps, storing files or credentials, or looking up framework APIs.

  • Reads credentials

We split this skill into the rules it gives an agent

11 rules. About 0 are common, 2 are distinctive, and 9 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 9

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read agent-native-docs for the lookup workflow (framework-search first, then the focused docs-search / source-search readers, and the rg …

    line 20
  2. Very specific:

    Before building common workspace or agent UI, read agent-native-toolkit to inventory existing public kits and installed package seams.

    line 29
  3. Very specific:

    All AI/LLM behavior goes through the app's agent chat.

    line 38
  4. Distinctive:

    Keep actions deterministic and focused.

    line 42
  5. Very specific:

    Only use useAgentChatContext, setAgentChatContextItem, listAgentChatContext, removeAgentChatContextItem, and clearAgentChatContext when UI …

    line 46
  6. Very specific:

    Read .agents/skills/delegate-to-agent/SKILL.md before building agent-driven UI or "AI" features.

    line 49
  7. Very specific:

    Put shared code in packages/shared only when multiple apps need it.

    line 51
  8. Very specific:

    Keep app-specific screens, actions, state, and skills inside apps/<app>.

    line 52
  9. Distinctive:

    Prefer framework defaults until the workspace has a real custom rule, component, plugin, action, or skill to share.

    line 72
  10. Very specific:

    Keep the Workspace files view for user-authored or user-requested resources.

    line 74
  11. Very specific:

    Use AGENTS.md or instructions/<slug>.md for always-on guardrails, skills/<slug>/SKILL.md for workspace skills, context/<slug>.md for …

    line 80

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Workspace Conventions

The long-form detail behind the workspace AGENTS.md core rules. Read this before adding shared code, storing files or secrets, creating workspace resources, or looking up framework APIs.

Framework Docs Lookup

Read agent-native-docs for the lookup workflow (framework-search first, then the focused docs-search / source-search readers, and the rg fallback).

The workspace-specific slugs it does not list are workspace and multi-app-workspace. Feature flags and other specialized workflows are optional; read their skill only when the app uses them. Use package docs for framework APIs, the package corpus for reusable framework/template patterns, and this AGENTS.md plus .agents/skills/ for workspace-specific conventions.

Before building common workspace or agent UI, read agent-native-toolkit to inventory existing public kits and installed package seams. Read customizing-agent-native before adapting shared UI. Use the supported ladder: configure → compose → eject the smallest unit → propose a shared seam. Preview before --apply, commit agent-native.ejections.json, and never edit node_modules or eject protected runtime contracts.

Shared Conventions

  • All AI/LLM behavior goes through the app's agent chat. UI and server code must not call model providers, AI SDK generateText() / streamText(), or other inline LLM APIs directly. Use sendToAgentChat() for local app-agent work, including hidden context and submit: false prefill/review flows. Keep actions deterministic and focused. If a workflow is framed as research, analysis, generation, recommendation, or synthesis, let the agent orchestrate provider/data actions in the open AgentSidebar instead of hiding the work in one opaque action or a separate follow-up textbox. Only use useAgentChatContext, setAgentChatContextItem, listAgentChatContext, removeAgentChatContextItem, and clearAgentChatContext when UI needs two-way sync with staged context chips. Read .agents/skills/delegate-to-agent/SKILL.md before building agent-driven UI or "AI" features.
  • Put shared code in packages/shared only when multiple apps need it.
  • Keep app-specific screens, actions, state, and skills inside apps/<app>.
  • SQL is for structured records, metadata, references, and searchable text. Store large files/blob payloads (base64, data: URLs, images, video/audio, PDFs, ZIPs, screenshots, thumbnails, session replay chunks) in configured file/blob storage and persist only URLs, ids, or handles.
  • Store shared runtime configuration in the workspace root .env; use apps/<app>/.env only for app-specific overrides. For public app behavior, prefer the default in agent-native.config.ts and use the deterministic AGENT_NATIVE_CONFIG_<UPPER_SNAKE_PATH> alias only when a non-secret value needs a deployment override. Never hardcode API keys, tokens, webhook URLs, signing secrets, private Builder/internal data, customer data, or credential-looking literals in source, docs, prompts, fixtures, application state, action responses, or generated app content. Use secrets/OAuth/runtime configuration and obvious placeholders in examples.
  • Each app deploys its own /* page function, and that function ships whatever the app's server bundle depends on — including a dependency only a background job uses. Before an app takes on a heavy runtime (headless browser, ffmpeg, media processing, ML), read .agents/skills/performance/SKILL.md §9 and keep that work in a background function or job. A dependency belonging to one app does not belong in packages/shared.
  • Prefer framework defaults until the workspace has a real custom rule, component, plugin, action, or skill to share.
  • Keep the Workspace files view for user-authored or user-requested resources. Agents may create hidden agent_scratch resources for temporary working notes, scripts, task plans, or intermediate outputs, but should promote them to normal workspace visibility only when the user explicitly asks to keep or manage the file.
  • Runtime-editable global resources can be managed from Dispatch Resources. Use AGENTS.md or instructions/<slug>.md for always-on guardrails, skills/<slug>/SKILL.md for workspace skills, context/<slug>.md for personas/positioning/messaging/company facts/brand guidelines, and agents/<slug>.md for custom agent profiles. Scope them to All apps when every workspace app should inherit them. All-app resources are inherited at runtime; do not copy or sync them into individual apps.
  • Which hosted first-party apps (Mail, Calendar, Content, ...) exist in the workspace is set by agent-native.builtinAgents in the root package.json: { "mode": "all" | "none" | "selected", "include": [...] } (absent means "all"; ids must be template names; restart agent-native dev after editing). It never touches mounted workspace apps or connected remote agents, and set-mcp-app-access stays a separate MCP routing permission.

Related Skills

  • adding-workspace-apps — Creating and mounting a new app under apps/.
  • agent-native-docs — The full docs and source-corpus lookup workflow.
  • agent-native-toolkit — Inventory of shared workspace and agent UI.
  • customizing-agent-native — The configure → compose → eject ladder.
  • delegate-to-agent — Routing every AI feature through the agent chat.
  • performance — Load cost, and (§9) cold-start artifact size per app.
  • secrets — Registering API keys and service credentials.
  • storing-data — Where structured data and large payloads belong.

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New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

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