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.a2a/agent.dsl.json Normal file
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{
"schema_version": "2026-06-04",
"language": "python",
"name": "robertseares",
"description": "A new A2A agent",
"version": "0.1.0",
"entrypoint": {
"module": "agent",
"class_name": "Robertseares",
"function": null,
"command": []
},
"skills": [
{
"name": "ask",
"description": "Ask the starter DeepAgent to answer with tool calls when useful",
"handler": "ask",
"tags": [],
"scopes": [],
"stream": false,
"policy": {
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"idempotent": false,
"max_retries": 0,
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"allow_scope_expansion": false,
"grant_mode": null,
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},
"input_schema": {
"type": "object",
"properties": {
"prompt": {
"type": "string"
}
},
"required": [
"prompt"
],
"additionalProperties": false
},
"output_schema": {
"type": "string"
}
}
],
"capabilities": {},
"input_modes": [
"application/json"
],
"output_modes": [
"application/json"
],
"required_secrets": [],
"required_env": [],
"consumer_setup": {
"fields": []
},
"runtime": {
"lifecycle": "ephemeral",
"state": "none",
"sandbox": "microsandbox",
"resources": {
"cpu": "100m",
"memory": "256Mi",
"gpu": 0,
"max_runtime_seconds": 600
},
"concurrency": 1,
"egress": {
"allow_hosts": [],
"allow_internal_services": [],
"deny_internet_by_default": true
},
"tools_used": [
"deepagents",
"langchain"
],
"llm_provisioning": "platform",
"pricing": {
"price_per_call_usd": 0.0,
"caller_pays_llm": true,
"notes": "Starter agent uses the caller's saved LLM credential via ctx.llm."
},
"wants_cp_jwt": false,
"platform_resources": {
"memory": null,
"databases": []
},
"apt_packages": []
},
"template_lineage": null,
"meta_agent_manifest": null,
"state_schema": null,
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"enabled": true,
"max_files": 64,
"allowed_modes": [
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},
"config_schema": {
"properties": {},
"title": "RobertsearesConfig",
"type": "object"
},
"auth": {
"model": "a2a_pack.auth.NoAuth",
"strategy": "public",
"principal_schema": {
"additionalProperties": false,
"description": "Public agent: no caller identity required.",
"properties": {},
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"type": "object"
},
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},
"metadata": {
"source": "python-a2a-pack",
"project_manifest": {
"name": "robertseares",
"version": "0.1.0",
"entrypoint": "agent:Robertseares",
"frontend": {
"type": "static-spa",
"path": "frontend",
"build": "npm run build",
"dist": "out",
"mount": "/",
"auth": "inherit"
}
}
}
}

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# robertseares
A new A2A agent
This project was scaffolded with `a2a init`. It starts as a DeepAgents-backed
A2A agent that uses the caller's saved LLM credential from `ctx.llm`.
`LLMProvisioning.PLATFORM` and `LLMProvisioning.CALLER_PROVIDED` both read that
same `ctx.llm` path. Do not read provider keys, LiteLLM master keys,
`OPENAI_API_KEY`, or `A2A_LITELLM_KEY` directly in agent code, and do not
substitute fake fallback API keys when `ctx.llm.api_key` is empty.
## Durable Files
A2A Cloud workspaces are grant-scoped and backed by MinIO. Files become durable
when your agent uses one of the platform-owned file paths:
- `ctx.workspace` for direct workspace reads and writes
- `ctx.write_artifact(...)` for explicit output artifacts
- `ctx.sandbox` for commands that read or write files in a sandbox
- `ctx.workspace_backend()` for framework file tools such as DeepAgents
DeepAgents has its own built-in file tools (`write_file`, `read_file`,
`edit_file`). Without an A2A backend, those tools write into LangGraph state
only, so files can appear to the agent but never reach MinIO or `/workspace`.
Keep this line when building DeepAgents graphs:
```python
backend = ctx.workspace_backend()
return create_a2a_deep_agent(ctx, backend=backend, tools=[...])
```
Invoke DeepAgents graphs with the starter recursion budget:
```python
state = await graph.ainvoke(
{"messages": [{"role": "user", "content": prompt}]},
config={"recursion_limit": 500},
)
```
The backend respects the caller's grant. In handoffs, generated files should go
through `ctx.workspace_backend()`, `ctx.write_artifact(...)`, or a sandbox helper
so they are mirrored to the caller workspace instead of becoming private virtual
files.
For stable, human-readable paths, write intentional outputs to
`/workspace/outputs/...` or `ctx.write_artifact(...)`. If sandboxed code writes
to process-local paths such as `/tmp/result.csv`, `/root`, or `/app`, the
platform captures changed rootfs files under `outputs/rootfs-captures/...` so
the caller can still download and inspect them.
When a skill needs to run real code, render media, convert files, or call a
CLI that writes outputs, use the workspace-mounted sandbox helpers:
```python
result = await ctx.workspace_shell(
"python script.py --out /tmp/result.txt",
image="python:3.11-slim",
timeout_seconds=120,
)
```
Do not rely on `asyncio.create_subprocess_exec(...)` for durable outputs. A
plain subprocess runs in the agent container, which is not mounted to the
caller workspace; files it creates in `/tmp` or the image filesystem can vanish
after the request. Use the sandbox helpers for any file-producing toolchain.
## DeepAgents Skills
If this project grows reusable workflow knowledge, add source-controlled skill
folders under `skills/<skill-name>/SKILL.md`. The starter's `_seed_runtime_skills`
helper copies those packaged skills into the invocation workspace and passes the
resulting source path to `create_a2a_deep_agent(..., skills=[...])`, which is
how DeepAgents discovers skills with progressive disclosure.
## Run Locally
```bash
python -m pip install -r requirements.txt
a2a dev
a2a test
a2a test --invoke --skill summarize --args-json '{"text":"hello"}'
a2a card
```
`a2a dev` loads `.env.local`, creates `.a2a/workspace/{inputs,outputs}`, serves
the same HTTP invoke/card/MCP endpoints as production, and hot reloads local
code. Files written through `ctx.workspace_backend()` land under
`.a2a/workspace/outputs` before you deploy.
## Auth
The template is public by default (`auth_model = NoAuth`). To require the
caller's app login, declare a typed auth model and resolver in `agent.py`.
Resolvers receive the inbound bearer token and return the principal exposed as
`ctx.auth`.
Hosted browser/direct invokes that use `LLMProvisioning.PLATFORM` still need an
A2A Cloud session so the runtime can mint a short-lived LLM/workspace grant for
that user. Agent-to-agent handoffs pass that grant explicitly.
```python
from a2a_pack import JWTAuth, OIDCUserInfoAuthResolver
auth_model = JWTAuth
auth_resolver = OIDCUserInfoAuthResolver(
"https://auth.example.com/oauth2/userinfo",
auth_model=JWTAuth,
)
```
For homegrown auth or SAML-backed apps, expose a bearer-token `/me` or
`/introspect` endpoint and use the same resolver contract.
## Deploy
```bash
a2a deploy
```

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# Project identity for `a2a deploy`. Most metadata (resources, scopes,
# secrets, workspace, etc.) lives on the Python class — this file only
# tells the CLI how to find it.
name: robertseares
version: 0.1.0
entrypoint: agent:Robertseares
expose:
public: true
# Optional platform resources:
# resources:
# memory:
# tiers: [kv, vector]
# namespace: robertseares
# databases:
# - name: app
# provider: neon
# engine: postgres
# env:
# url: DATABASE_URL
frontend:
type: static-spa
path: frontend
build: npm run build
dist: out
mount: /
auth: inherit

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"""robertseares agent.
Starter stack:
- DeepAgents for tool-calling orchestration
- Caller-provided LLM credentials via ctx.llm
- A tiny model-call middleware hook you can replace with tracing,
routing, rate limits, or policy checks
"""
from __future__ import annotations
import json
from pathlib import Path
from typing import Any
from pydantic import BaseModel
from a2a_pack import (
A2AAgent,
LLMProvisioning,
NoAuth,
Pricing,
RunContext,
WorkspaceAccess,
WorkspaceMode,
skill,
)
from a2a_pack.context import LLMCreds
class RobertsearesConfig(BaseModel):
pass
SYSTEM_PROMPT = """\
You are a compact tool-calling agent.
Use the text_stats tool when the user asks about text, counts, summaries,
or anything where exact length/word numbers would help. Mention tool results
briefly instead of dumping raw JSON.
"""
RUNTIME_SKILLS_DIR = "robertseares/.deepagents/skills/"
DEEPAGENTS_RECURSION_LIMIT = 500
class Robertseares(A2AAgent[RobertsearesConfig, NoAuth]):
name = "robertseares"
description = "A new A2A agent"
version = "0.1.0"
config_model = RobertsearesConfig
auth_model = NoAuth
# Hosted generated agents read the caller's saved LLM credential through
# ctx.llm. The platform may proxy that credential through LiteLLM, but agent
# code never reads provider keys, LiteLLM master keys, or OPENAI_API_KEY
# directly.
llm_provisioning = LLMProvisioning.PLATFORM
pricing = Pricing(
price_per_call_usd=0.0,
caller_pays_llm=True,
notes="Starter agent uses the caller's saved LLM credential via ctx.llm.",
)
workspace_access = WorkspaceAccess.dynamic(
max_files=64,
allowed_modes=(WorkspaceMode.READ_ONLY, WorkspaceMode.READ_WRITE_OVERLAY),
require_reason=False,
)
tools_used = ("deepagents", "langchain")
@skill(description="Ask the starter DeepAgent to answer with tool calls when useful")
async def ask(self, ctx: RunContext[NoAuth], prompt: str) -> str:
creds = ctx.llm
await ctx.emit_progress(f"llm: {creds.model} via {creds.source}")
if not creds.api_key:
return (
"LLM key required. Add an LLM credential in Settings > LLM "
"credentials before running this agent; for local --invoke "
"runs set AGENT_LLM_KEY."
)
graph = self._build_deep_agent(ctx=ctx, creds=creds)
state = await graph.ainvoke(
{"messages": [{"role": "user", "content": prompt}]},
config={"recursion_limit": DEEPAGENTS_RECURSION_LIMIT},
)
await ctx.emit_progress("deepagent finished")
return _last_message_text(state)
def _build_deep_agent(
self,
*,
ctx: RunContext[NoAuth],
creds: LLMCreds,
) -> Any:
# Lazy imports keep `a2a card` usable before local dependencies are
# installed. `a2a deploy` installs requirements.txt during the build.
from a2a_pack.deepagents import create_a2a_deep_agent
from langchain.agents.middleware import wrap_model_call
from langchain_core.tools import tool
@tool
def text_stats(text: str) -> str:
"""Return exact word, character, and line counts for text."""
words = [part for part in text.split() if part.strip()]
return json.dumps(
{
"characters": len(text),
"words": len(words),
"lines": len(text.splitlines()) or 1,
}
)
@wrap_model_call
async def log_model_call(request: Any, handler: Any) -> Any:
messages = request.state.get("messages", [])
print(
"[middleware] model_call "
f"model={creds.model} source={creds.source} messages={len(messages)}"
)
return await handler(request)
backend = ctx.workspace_backend()
skill_sources = _seed_runtime_skills(backend, ctx)
# create_a2a_deep_agent resolves provider:model strings with
# langchain.init_chat_model from ctx.llm, preserving LiteLLM routing,
# provider-specific extra body, and runtime model overrides.
return create_a2a_deep_agent(
ctx,
creds=creds,
backend=backend,
skills=skill_sources or None,
tools=[text_stats],
middleware=[log_model_call],
system_prompt=SYSTEM_PROMPT,
)
def _runtime_skills_root(ctx: RunContext[Any]) -> str:
workspace = getattr(ctx, "_workspace", None)
prefixes = tuple(getattr(workspace, "write_prefixes", ()) or ())
if not prefixes:
outputs_prefix = getattr(workspace, "outputs_prefix", None)
prefixes = (outputs_prefix or "outputs/",)
prefix = str(prefixes[0]).strip("/")
return f"/{prefix}/{RUNTIME_SKILLS_DIR}" if prefix else f"/{RUNTIME_SKILLS_DIR}"
def _seed_runtime_skills(backend: Any, ctx: RunContext[Any]) -> list[str]:
"""Copy packaged DeepAgents skills into the invocation workspace.
DeepAgents loads skills from its backend, while source-controlled
``skills/`` folders live in the image. This bridge lets generated agents
ship reusable SKILL.md bundles without giving up durable A2A workspace
files.
"""
root = Path(__file__).parent / "skills"
if not root.exists():
return []
runtime_skills_root = _runtime_skills_root(ctx)
uploads: list[tuple[str, bytes]] = []
for path in root.rglob("*"):
if path.is_file():
rel = path.relative_to(root).as_posix()
uploads.append((runtime_skills_root + rel, path.read_bytes()))
if uploads:
backend.upload_files(uploads)
return [runtime_skills_root]
return []
def _last_message_text(state: dict[str, Any]) -> str:
messages = state.get("messages") or []
if not messages:
return json.dumps(state, default=str)
content = getattr(messages[-1], "content", None)
if isinstance(content, str):
return content
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, dict):
text = item.get("text") or item.get("content")
if text:
parts.append(str(text))
elif item:
parts.append(str(item))
return "\n".join(parts) if parts else json.dumps(content, default=str)
return str(content or messages[-1])

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generateStaticParams?: Function
revalidate?: RevalidateRange<TEntry> | false
dynamic?: 'auto' | 'force-dynamic' | 'error' | 'force-static'
dynamicParams?: boolean
fetchCache?: 'auto' | 'force-no-store' | 'only-no-store' | 'default-no-store' | 'default-cache' | 'only-cache' | 'force-cache'
preferredRegion?: 'auto' | 'global' | 'home' | string | string[]
runtime?: 'nodejs' | 'experimental-edge' | 'edge'
maxDuration?: number
metadata?: any
generateMetadata?: Function
viewport?: any
generateViewport?: Function
experimental_ppr?: boolean
}, TEntry, ''>>()
// Check the prop type of the entry function
checkFields<Diff<LayoutProps, FirstArg<TEntry['default']>, 'default'>>()
// Check the arguments and return type of the generateMetadata function
if ('generateMetadata' in entry) {
checkFields<Diff<LayoutProps, FirstArg<MaybeField<TEntry, 'generateMetadata'>>, 'generateMetadata'>>()
checkFields<Diff<ResolvingMetadata, SecondArg<MaybeField<TEntry, 'generateMetadata'>>, 'generateMetadata'>>()
}
// Check the arguments and return type of the generateViewport function
if ('generateViewport' in entry) {
checkFields<Diff<LayoutProps, FirstArg<MaybeField<TEntry, 'generateViewport'>>, 'generateViewport'>>()
checkFields<Diff<ResolvingViewport, SecondArg<MaybeField<TEntry, 'generateViewport'>>, 'generateViewport'>>()
}
// Check the arguments and return type of the generateStaticParams function
if ('generateStaticParams' in entry) {
checkFields<Diff<{ params: SegmentParams }, FirstArg<MaybeField<TEntry, 'generateStaticParams'>>, 'generateStaticParams'>>()
checkFields<Diff<{ __tag__: 'generateStaticParams', __return_type__: any[] | Promise<any[]> }, { __tag__: 'generateStaticParams', __return_type__: ReturnType<MaybeField<TEntry, 'generateStaticParams'>> }>>()
}
export interface PageProps {
params?: Promise<SegmentParams>
searchParams?: Promise<any>
}
export interface LayoutProps {
children?: React.ReactNode
params?: Promise<SegmentParams>
}
// =============
// Utility types
type RevalidateRange<T> = T extends { revalidate: any } ? NonNegative<T['revalidate']> : never
// If T is unknown or any, it will be an empty {} type. Otherwise, it will be the same as Omit<T, keyof Base>.
type OmitWithTag<T, K extends keyof any, _M> = Omit<T, K>
type Diff<Base, T extends Base, Message extends string = ''> = 0 extends (1 & T) ? {} : OmitWithTag<T, keyof Base, Message>
type FirstArg<T extends Function> = T extends (...args: [infer T, any]) => any ? unknown extends T ? any : T : never
type SecondArg<T extends Function> = T extends (...args: [any, infer T]) => any ? unknown extends T ? any : T : never
type MaybeField<T, K extends string> = T extends { [k in K]: infer G } ? G extends Function ? G : never : never
function checkFields<_ extends { [k in keyof any]: never }>() {}
// https://github.com/sindresorhus/type-fest
type Numeric = number | bigint
type Zero = 0 | 0n
type Negative<T extends Numeric> = T extends Zero ? never : `${T}` extends `-${string}` ? T : never
type NonNegative<T extends Numeric> = T extends Zero ? T : Negative<T> extends never ? T : '__invalid_negative_number__'

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// File: /Users/robert/MicroCash/agents/robertseares/frontend/app/page.jsx
import * as entry from '../../../app/page.js'
import type { ResolvingMetadata, ResolvingViewport } from 'next/dist/lib/metadata/types/metadata-interface.js'
type TEntry = typeof import('../../../app/page.js')
type SegmentParams<T extends Object = any> = T extends Record<string, any>
? { [K in keyof T]: T[K] extends string ? string | string[] | undefined : never }
: T
// Check that the entry is a valid entry
checkFields<Diff<{
default: Function
config?: {}
generateStaticParams?: Function
revalidate?: RevalidateRange<TEntry> | false
dynamic?: 'auto' | 'force-dynamic' | 'error' | 'force-static'
dynamicParams?: boolean
fetchCache?: 'auto' | 'force-no-store' | 'only-no-store' | 'default-no-store' | 'default-cache' | 'only-cache' | 'force-cache'
preferredRegion?: 'auto' | 'global' | 'home' | string | string[]
runtime?: 'nodejs' | 'experimental-edge' | 'edge'
maxDuration?: number
metadata?: any
generateMetadata?: Function
viewport?: any
generateViewport?: Function
experimental_ppr?: boolean
}, TEntry, ''>>()
// Check the prop type of the entry function
checkFields<Diff<PageProps, FirstArg<TEntry['default']>, 'default'>>()
// Check the arguments and return type of the generateMetadata function
if ('generateMetadata' in entry) {
checkFields<Diff<PageProps, FirstArg<MaybeField<TEntry, 'generateMetadata'>>, 'generateMetadata'>>()
checkFields<Diff<ResolvingMetadata, SecondArg<MaybeField<TEntry, 'generateMetadata'>>, 'generateMetadata'>>()
}
// Check the arguments and return type of the generateViewport function
if ('generateViewport' in entry) {
checkFields<Diff<PageProps, FirstArg<MaybeField<TEntry, 'generateViewport'>>, 'generateViewport'>>()
checkFields<Diff<ResolvingViewport, SecondArg<MaybeField<TEntry, 'generateViewport'>>, 'generateViewport'>>()
}
// Check the arguments and return type of the generateStaticParams function
if ('generateStaticParams' in entry) {
checkFields<Diff<{ params: SegmentParams }, FirstArg<MaybeField<TEntry, 'generateStaticParams'>>, 'generateStaticParams'>>()
checkFields<Diff<{ __tag__: 'generateStaticParams', __return_type__: any[] | Promise<any[]> }, { __tag__: 'generateStaticParams', __return_type__: ReturnType<MaybeField<TEntry, 'generateStaticParams'>> }>>()
}
export interface PageProps {
params?: Promise<SegmentParams>
searchParams?: Promise<any>
}
export interface LayoutProps {
children?: React.ReactNode
params?: Promise<SegmentParams>
}
// =============
// Utility types
type RevalidateRange<T> = T extends { revalidate: any } ? NonNegative<T['revalidate']> : never
// If T is unknown or any, it will be an empty {} type. Otherwise, it will be the same as Omit<T, keyof Base>.
type OmitWithTag<T, K extends keyof any, _M> = Omit<T, K>
type Diff<Base, T extends Base, Message extends string = ''> = 0 extends (1 & T) ? {} : OmitWithTag<T, keyof Base, Message>
type FirstArg<T extends Function> = T extends (...args: [infer T, any]) => any ? unknown extends T ? any : T : never
type SecondArg<T extends Function> = T extends (...args: [any, infer T]) => any ? unknown extends T ? any : T : never
type MaybeField<T, K extends string> = T extends { [k in K]: infer G } ? G extends Function ? G : never : never
function checkFields<_ extends { [k in keyof any]: never }>() {}
// https://github.com/sindresorhus/type-fest
type Numeric = number | bigint
type Zero = 0 | 0n
type Negative<T extends Numeric> = T extends Zero ? never : `${T}` extends `-${string}` ? T : never
type NonNegative<T extends Numeric> = T extends Zero ? T : Negative<T> extends never ? T : '__invalid_negative_number__'

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// Type definitions for Next.js cacheLife configs
declare module 'next/cache' {
export { unstable_cache } from 'next/dist/server/web/spec-extension/unstable-cache'
export {
revalidateTag,
revalidatePath,
unstable_expireTag,
unstable_expirePath,
} from 'next/dist/server/web/spec-extension/revalidate'
export { unstable_noStore } from 'next/dist/server/web/spec-extension/unstable-no-store'
/**
* Cache this `"use cache"` for a timespan defined by the `"default"` profile.
* ```
* stale: 300 seconds (5 minutes)
* revalidate: 900 seconds (15 minutes)
* expire: never
* ```
*
* This cache may be stale on clients for 5 minutes before checking with the server.
* If the server receives a new request after 15 minutes, start revalidating new values in the background.
* It lives for the maximum age of the server cache. If this entry has no traffic for a while, it may serve an old value the next request.
*/
export function unstable_cacheLife(profile: "default"): void
/**
* Cache this `"use cache"` for a timespan defined by the `"seconds"` profile.
* ```
* stale: 30 seconds
* revalidate: 1 seconds
* expire: 60 seconds (1 minute)
* ```
*
* This cache may be stale on clients for 30 seconds before checking with the server.
* If the server receives a new request after 1 seconds, start revalidating new values in the background.
* If this entry has no traffic for 1 minute it will expire. The next request will recompute it.
*/
export function unstable_cacheLife(profile: "seconds"): void
/**
* Cache this `"use cache"` for a timespan defined by the `"minutes"` profile.
* ```
* stale: 300 seconds (5 minutes)
* revalidate: 60 seconds (1 minute)
* expire: 3600 seconds (1 hour)
* ```
*
* This cache may be stale on clients for 5 minutes before checking with the server.
* If the server receives a new request after 1 minute, start revalidating new values in the background.
* If this entry has no traffic for 1 hour it will expire. The next request will recompute it.
*/
export function unstable_cacheLife(profile: "minutes"): void
/**
* Cache this `"use cache"` for a timespan defined by the `"hours"` profile.
* ```
* stale: 300 seconds (5 minutes)
* revalidate: 3600 seconds (1 hour)
* expire: 86400 seconds (1 day)
* ```
*
* This cache may be stale on clients for 5 minutes before checking with the server.
* If the server receives a new request after 1 hour, start revalidating new values in the background.
* If this entry has no traffic for 1 day it will expire. The next request will recompute it.
*/
export function unstable_cacheLife(profile: "hours"): void
/**
* Cache this `"use cache"` for a timespan defined by the `"days"` profile.
* ```
* stale: 300 seconds (5 minutes)
* revalidate: 86400 seconds (1 day)
* expire: 604800 seconds (1 week)
* ```
*
* This cache may be stale on clients for 5 minutes before checking with the server.
* If the server receives a new request after 1 day, start revalidating new values in the background.
* If this entry has no traffic for 1 week it will expire. The next request will recompute it.
*/
export function unstable_cacheLife(profile: "days"): void
/**
* Cache this `"use cache"` for a timespan defined by the `"weeks"` profile.
* ```
* stale: 300 seconds (5 minutes)
* revalidate: 604800 seconds (1 week)
* expire: 2592000 seconds (30 days)
* ```
*
* This cache may be stale on clients for 5 minutes before checking with the server.
* If the server receives a new request after 1 week, start revalidating new values in the background.
* If this entry has no traffic for 30 days it will expire. The next request will recompute it.
*/
export function unstable_cacheLife(profile: "weeks"): void
/**
* Cache this `"use cache"` for a timespan defined by the `"max"` profile.
* ```
* stale: 300 seconds (5 minutes)
* revalidate: 2592000 seconds (30 days)
* expire: never
* ```
*
* This cache may be stale on clients for 5 minutes before checking with the server.
* If the server receives a new request after 30 days, start revalidating new values in the background.
* It lives for the maximum age of the server cache. If this entry has no traffic for a while, it may serve an old value the next request.
*/
export function unstable_cacheLife(profile: "max"): void
/**
* Cache this `"use cache"` using a custom timespan.
* ```
* stale: ... // seconds
* revalidate: ... // seconds
* expire: ... // seconds
* ```
*
* This is similar to Cache-Control: max-age=`stale`,s-max-age=`revalidate`,stale-while-revalidate=`expire-revalidate`
*
* If a value is left out, the lowest of other cacheLife() calls or the default, is used instead.
*/
export function unstable_cacheLife(profile: {
/**
* This cache may be stale on clients for ... seconds before checking with the server.
*/
stale?: number,
/**
* If the server receives a new request after ... seconds, start revalidating new values in the background.
*/
revalidate?: number,
/**
* If this entry has no traffic for ... seconds it will expire. The next request will recompute it.
*/
expire?: number
}): void
export { cacheTag as unstable_cacheTag } from 'next/dist/server/use-cache/cache-tag'
}

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{"type": "module"}

57
frontend/.next/types/routes.d.ts vendored Normal file
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// This file is generated automatically by Next.js
// Do not edit this file manually
type AppRoutes = never
type PageRoutes = never
type LayoutRoutes = "/"
type RedirectRoutes = never
type RewriteRoutes = never
type Routes = AppRoutes | PageRoutes | LayoutRoutes | RedirectRoutes | RewriteRoutes
interface ParamMap {
"/": {}
}
export type ParamsOf<Route extends Routes> = ParamMap[Route]
interface LayoutSlotMap {
"/": never
}
export type { AppRoutes, PageRoutes, LayoutRoutes, RedirectRoutes, RewriteRoutes, ParamMap }
declare global {
/**
* Props for Next.js App Router page components
* @example
* ```tsx
* export default function Page(props: PageProps<'/blog/[slug]'>) {
* const { slug } = await props.params
* return <div>Blog post: {slug}</div>
* }
* ```
*/
interface PageProps<AppRoute extends AppRoutes> {
params: Promise<ParamMap[AppRoute]>
searchParams: Promise<Record<string, string | string[] | undefined>>
}
/**
* Props for Next.js App Router layout components
* @example
* ```tsx
* export default function Layout(props: LayoutProps<'/dashboard'>) {
* return <div>{props.children}</div>
* }
* ```
*/
type LayoutProps<LayoutRoute extends LayoutRoutes> = {
params: Promise<ParamMap[LayoutRoute]>
children: React.ReactNode
} & {
[K in LayoutSlotMap[LayoutRoute]]: React.ReactNode
}
}

16
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// This file is generated automatically by Next.js
// Do not edit this file manually
// This file validates that all pages and layouts export the correct types

282
frontend/app/globals.css Normal file
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@import "tailwindcss";
:root {
color-scheme: light;
font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif;
background: #f4f1ec;
color: #191816;
}
* {
box-sizing: border-box;
}
html {
scroll-behavior: smooth;
}
body {
margin: 0;
min-height: 100vh;
background:
linear-gradient(90deg, rgba(25, 24, 22, 0.05) 1px, transparent 1px),
linear-gradient(180deg, rgba(25, 24, 22, 0.05) 1px, transparent 1px),
#f4f1ec;
background-size: 44px 44px;
}
main {
overflow: hidden;
}
h1,
h2,
h3,
p {
margin-top: 0;
}
p {
color: #4d4840;
font-size: 18px;
line-height: 1.7;
}
.hero {
min-height: 92vh;
display: flex;
align-items: flex-end;
padding: 56px 28px;
background:
linear-gradient(135deg, rgba(22, 82, 73, 0.14), transparent 48%),
linear-gradient(180deg, rgba(244, 241, 236, 0.52), #f4f1ec 84%),
url("https://images.unsplash.com/photo-1497366754035-f200968a6e72?auto=format&fit=crop&w=2200&q=85");
background-position: center;
background-size: cover;
}
.hero-inner {
width: min(1120px, 100%);
margin: 0 auto;
padding-top: 18vh;
}
.eyebrow {
margin-bottom: 14px;
color: #0f6c5b;
font-size: 12px;
font-weight: 800;
letter-spacing: 0;
text-transform: uppercase;
}
h1 {
max-width: 980px;
margin-bottom: 24px;
color: #171512;
font-size: clamp(64px, 11vw, 148px);
line-height: 0.88;
letter-spacing: 0;
overflow-wrap: anywhere;
}
h2 {
margin-bottom: 18px;
color: #1c1a17;
font-size: clamp(34px, 5vw, 68px);
line-height: 0.98;
letter-spacing: 0;
}
.lede {
max-width: 760px;
margin-bottom: 18px;
color: #1f352f;
font-size: clamp(28px, 4vw, 48px);
line-height: 1.08;
font-weight: 750;
}
.intro {
max-width: 820px;
margin-bottom: 0;
color: #27231e;
font-size: 21px;
line-height: 1.65;
}
.section {
padding: 96px 28px;
}
.content-grid {
width: min(1120px, 100%);
margin: 0 auto;
display: grid;
grid-template-columns: minmax(240px, 0.8fr) minmax(0, 1.2fr);
gap: 56px;
align-items: start;
}
.copy p:last-child {
margin-bottom: 0;
}
.lead-copy {
margin-bottom: 28px;
}
.question-band {
background: #17231f;
color: #f9f6ef;
}
.question {
width: min(980px, 100%);
margin: 0 auto;
}
.question .eyebrow {
color: #71d7b8;
}
.question h2 {
color: #fffaf2;
}
.question p {
max-width: 760px;
margin-bottom: 0;
color: #d9e2dc;
}
.pill-grid,
.interest-grid {
display: flex;
flex-wrap: wrap;
gap: 10px;
}
.pill-grid span,
.interest-grid span {
border: 1px solid rgba(25, 24, 22, 0.18);
border-radius: 8px;
background: rgba(255, 255, 255, 0.56);
padding: 11px 13px;
color: #25221d;
font-size: 15px;
font-weight: 700;
}
.split-band {
width: min(1120px, calc(100% - 56px));
margin: 0 auto;
padding-right: 0;
padding-left: 0;
display: grid;
grid-template-columns: repeat(2, minmax(0, 1fr));
gap: 1px;
background: rgba(25, 24, 22, 0.18);
}
.split-band article {
min-height: 520px;
padding: 42px;
background: #fffdf8;
}
.split-band article:first-child {
background: #e7eee8;
}
.split-band h2 {
font-size: clamp(32px, 4vw, 54px);
}
.clean-list {
display: grid;
gap: 12px;
margin: 28px 0 0;
padding: 0;
list-style: none;
}
.clean-list li {
border-top: 1px solid rgba(25, 24, 22, 0.18);
padding-top: 12px;
color: #25221d;
font-size: 17px;
font-weight: 800;
}
.interests {
width: min(1120px, 100%);
margin: 0 auto;
}
.interests h2 {
max-width: 760px;
}
.connect {
width: min(1120px, calc(100% - 56px));
margin: 0 auto 56px;
border-radius: 8px;
background: #171512;
padding: 56px;
}
.connect .eyebrow {
color: #71d7b8;
}
.connect h2 {
max-width: 920px;
color: #fffaf2;
}
.connect p {
max-width: 720px;
margin-bottom: 0;
color: #d8d0c3;
}
@media (max-width: 820px) {
.hero {
min-height: 86vh;
padding: 36px 20px;
}
.hero-inner {
padding-top: 12vh;
}
.section {
padding: 64px 20px;
}
.content-grid,
.split-band {
grid-template-columns: 1fr;
gap: 28px;
}
.split-band {
width: min(100% - 40px, 1120px);
}
.split-band article {
min-height: auto;
padding: 28px;
}
.connect {
width: min(100% - 40px, 1120px);
padding: 32px 24px;
}
p,
.intro {
font-size: 17px;
}
}

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import "./globals.css";
export const metadata = {
title: "Robert Seares",
description: "Software engineer, engineering leader, founder, and product builder."
};
export default function RootLayout({ children }) {
return (
<html lang="en">
<body>{children}</body>
</html>
);
}

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const focusAreas = [
"Artificial Intelligence",
"Cloud Infrastructure",
"Distributed Systems",
"Developer Platforms",
"Product Engineering",
"Startup Operations",
"Automation",
"Technical Leadership",
];
const values = [
"Ownership over bureaucracy",
"Speed over perfection",
"Simplicity over complexity",
"Learning over ego",
"Execution over presentations",
];
const interests = [
"AI agents and autonomous systems",
"Cloud-native platforms",
"Scientific computing",
"Biotechnology",
"Startup strategy",
"Developer experience",
"Infrastructure automation",
"Human-computer collaboration",
];
export default function Home() {
return (
<main>
<section className="hero">
<div className="hero-inner">
<p className="eyebrow">Software engineer, founder, product builder</p>
<h1>Robert Seares</h1>
<p className="lede">I build companies, software, and systems.</p>
<p className="intro">
I am a software engineer, engineering leader, founder, and product
builder currently living in Brazil with my wife and two children.
Over the last decade I have worked across startups, AI, biotech,
consumer products, infrastructure, and automation, always gravitating
toward difficult technical problems where software can create
outsized leverage.
</p>
</div>
</section>
<section className="section narrative">
<div className="content-grid">
<div>
<p className="eyebrow">Today</p>
<h2>Engineering at Ark Biotech</h2>
</div>
<div className="copy">
<p>
Today I lead software engineering at Ark Biotech, where I help
build the infrastructure, applications, simulation tooling, and AI
systems powering next-generation biomanufacturing.
</p>
<p>
My work spans cloud infrastructure, developer platforms,
simulation systems, machine learning applications, frontend
architecture, backend services, and engineering leadership.
</p>
</div>
</div>
</section>
<section className="section question-band">
<div className="question">
<p className="eyebrow">The question</p>
<h2>How do we make it dramatically easier for people to build useful things?</h2>
<p>
That question has led me through projects ranging from AI systems
and developer platforms to restaurant software, biotechnology
infrastructure, and autonomous agents.
</p>
</div>
</section>
<section className="section">
<div className="content-grid">
<div>
<p className="eyebrow">What I do</p>
<h2>Systems that scale from idea to business</h2>
</div>
<div>
<p className="copy lead-copy">
I enjoy building systems that can scale from a single user to
thousands, and from a proof of concept to a business. My preferred
stack is Python, TypeScript, Kubernetes, FastAPI, React,
PostgreSQL, cloud-native infrastructure, and AI-powered workflows.
</p>
<div className="pill-grid">
{focusAreas.map((area) => (
<span key={area}>{area}</span>
))}
</div>
</div>
</div>
</section>
<section className="section split-band">
<article>
<p className="eyebrow">Philosophy</p>
<h2>Software should create leverage.</h2>
<p>
The best technology removes complexity rather than adding it. Great
systems are understandable, maintainable, and useful. Great
companies solve real problems. Great engineers ship.
</p>
<ul className="clean-list">
{values.map((value) => (
<li key={value}>{value}</li>
))}
</ul>
</article>
<article>
<p className="eyebrow">Building</p>
<h2>A laptop, an idea, and enough persistence.</h2>
<p>
Outside of my day job, I spend most of my time building. I have
launched products in AI, SaaS, developer tooling, restaurant
technology, and automation. Some succeeded, some failed, and all of
them taught me something valuable.
</p>
<p>
What keeps me motivated is the same thing that motivated me when I
started writing software: the ability to create something from
nothing.
</p>
</article>
</section>
<section className="section">
<div className="content-grid">
<div>
<p className="eyebrow">Life</p>
<h2>Countryside of Sao Paulo, Brazil</h2>
</div>
<div className="copy">
<p>
When I am not building software, I am spending time with my
family, exploring business ideas, studying technology, lifting
weights, reading about startups, or working on the next project
that probably should not exist but sounds too interesting not to
build.
</p>
</div>
</div>
</section>
<section className="section interests">
<div>
<p className="eyebrow">Current interests</p>
<h2>Problems worth paying attention to</h2>
</div>
<div className="interest-grid">
{interests.map((interest) => (
<span key={interest}>{interest}</span>
))}
</div>
</section>
<section className="section connect">
<p className="eyebrow">Connect</p>
<h2>If you are building something ambitious, I would love to hear about it.</h2>
<p>
I am always interested in talking with builders, founders, engineers,
and people working on difficult problems.
</p>
</section>
</main>
);
}

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{
"compilerOptions": {
"baseUrl": "."
}
}

6
frontend/next.config.mjs Normal file
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const nextConfig = {
output: "export",
trailingSlash: true,
};
export default nextConfig;

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frontend/package.json Normal file
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{
"name": "robertseares-frontend",
"private": true,
"version": "0.1.0",
"scripts": {
"dev": "next dev --hostname 0.0.0.0 --port 3000",
"build": "next build",
"start": "next start"
},
"dependencies": {
"next": "^15.3.0",
"react": "^19.0.0",
"react-dom": "^19.0.0"
},
"devDependencies": {
"@tailwindcss/postcss": "^4.3.0",
"postcss": "^8.5.15",
"tailwindcss": "^4.3.0"
}
}

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frontend/postcss.config.mjs Normal file
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const config = {
plugins: {
"@tailwindcss/postcss": {},
},
};
export default config;

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frontend/public/.gitkeep Normal file
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requirements.txt Normal file
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# a2a-pack is auto-installed by the deploy build.
# These starter deps power the DeepAgents tool-calling example in agent.py.
deepagents>=0.5.0
langchain>=0.3
langchain-openai>=0.2
langgraph>=0.6