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workflows for your codebase, built on [OpenCode](https://opencode.ai).","maintainers":[{"email":"fkschott@gmail.com","name":"fredkschott"},{"email":"matthew@matthewphillips.info","name":"matthewp"}],"readme":"# @flue/client\n\nAI-powered workflows for your codebase, built on [OpenCode](https://opencode.ai).\n\n## Install\n\n```bash\nbun install @flue/client\nnpm install @flue/client\npnpm install @flue/client\n```\n\n## Usage\n\n```ts\n// .flue/workflows/issue-triage.ts\nimport type { FlueClient } from '@flue/client';\n\nexport default async function triage(flue: FlueClient, args: { issueNumber: number }) {\n  const issue = await flue.shell(`gh issue view ${args.issueNumber} --json title,body`);\n  const result = await flue.skill('triage/diagnose.md', {\n    args: { issueNumber: args.issueNumber },\n  });\n  const comment = await flue.prompt(`Summarize the triage for: ${issue.stdout}`);\n  await flue.shell(`gh issue comment ${args.issueNumber} --body-file -`, { stdin: comment });\n}\n```\n\n## API\n\n### `flue.shell(command, options?)`\n\nRun a shell command in the target environment. Returns `{ stdout, stderr, exitCode }`.\n\n```ts\nconst result = await flue.shell('pnpm test');\nconst result = await flue.shell('cat -', { stdin: 'hello' });\n```\n\nOptions: `env`, `stdin`, `cwd`, `timeout`\n\n### `flue.skill(name, options?)`\n\nDelegate a task to an AI agent using a skill file from `.agents/skills/`. The agent reads the skill instructions and works autonomously.\n\n```ts\n// Fire-and-forget (no return value)\nawait flue.skill('triage/reproduce.md', { args: { issueNumber: 123 } });\n\n// With a typed result (via Valibot schema)\nconst result = await flue.skill('triage/diagnose.md', {\n  result: v.object({ confidence: v.picklist(['high', 'medium', 'low']) }),\n});\n```\n\nOptions: `args`, `result`, `model`\n\n### `flue.prompt(text, options?)`\n\nSend a one-off prompt to an AI agent. Like `skill()` but inline — no skill file needed.\n\n```ts\nawait flue.prompt('Refactor the tests in src/utils/ to use vitest');\n\nconst summary = await flue.prompt('Summarize these test failures: ...', {\n  result: v.string(),\n});\n```\n\nOptions: `result`, `model`\n\n## Proxies (Sandbox Mode)\n\nIn sandbox mode, the AI agent runs inside a sandbox container with no access to sensitive host credentials. Proxies let the sandbox talk to external services without leaking any actual credentials into the sandbox.\n\nFlue ships with built-in presets for popular services. Every proxy supports an access control policy (`policy`) option for advanced control over what the sandbox has access to do. Built-in levels like `'allow-read'` and `'allow-all'` cover common service-specific policy rules, and you can extend them with explicit allow/deny rules for fine-grained control:\n\n```ts\nimport { anthropic, github } from '@flue/client/proxies';\n\nexport const proxies = {\n  anthropic: anthropic(),\n  github: github({\n    policy: {\n      base: 'allow-read',\n      allow: [{ method: 'POST', path: '/repos/withastro/astro/issues/*/comments', limit: 1 }],\n    },\n  }),\n};\n```\n","readmeFilename":"README.md"}