@merkie/agentic

A resilience, storage, and observability harness for LLM agents on the Vercel AI SDK + OpenRouter.

Most AI SDK setups are bring-your-own-everything: every project re-implements retry loops, chat persistence, crash recovery, compaction, and cost tracking — slightly differently, with the same bugs. @merkie/agentic ships that plumbing once, battle-tested, so your code is just models, prompts, and tools.

What the harness guarantees:

• Runs don't fail when waiting a second would have saved them. Transient provider errors (429s, 5xxs, severed SSE streams, stalled connections) are classified and retried with capped exponential backoff (server Retry-After wins). Deterministic errors — billing, auth, policy, malformed requests, context overflow — fail fast instead of burning credits in a retry loop.
• Runs survive process restarts. Every model step is persisted the moment it finishes; the agent loop is stateless over an append-only event ledger, so recovery from a SIGKILL mid-run is just "run the loop again". Bring your own storage (Prisma, SQLite, Redis…) by implementing two methods; JSONL file storage is built in.
• Workflows have guaranteed outcomes. task() gives the model submit_deliverable + cancel_task, validates the deliverable with zod inside the tool (validation errors go back to the model as tool results it can fix — no memoryless structured-output retries), and pokes the model if it ends its turn without calling a terminal tool. You always get submitted | cancelled | failed, never a throw.
• Chats outlive the context window. Compaction triggers on real provider-reported token counts against the model's actual context window (fetched from OpenRouter), summarizes into a hand-off message, and keeps going — silently between turns, or mid-run for agents deep in a task.
• Cost is tracked correctly, including BYOK: OpenRouter credits report cost; BYOK reports the provider charge in upstream_inference_cost. Per-step usage/cost is persisted, aggregated per run and per session.

Install

npm install @merkie/agentic ai @openrouter/ai-sdk-provider zod

ai (v6), @openrouter/ai-sdk-provider, and zod (v4) are peer dependencies. Reads OPENROUTER_API_KEY from the environment by default.

The harness in 30 seconds

import { createAgentic, fileStorage } from "@merkie/agentic";
import { tool } from "ai";
import { z } from "zod";

const agentic = createAgentic({ storage: fileStorage("./.agentic") });

// ── durable chat ──────────────────────────────────────────────────────
const chat = agentic.session("chat:user-123", {
  model: "qwen/qwen3.7-max",
  system: "You are a helpful assistant.",
  tools: { /* your tools */ },
  compaction: { limit: 0.3 },          // compact at 30% of context window
});
const reply = await chat.send("hey!", { onPart: (p) => {/* stream to UI */} });

// after a crash/deploy, on boot:
for (const id of await agentic.interruptedSessions()) {
  // re-supply the agent config and pick up where the run left off
  await agentic.session(id, myAgentFor(id)).resume();
}

// ── workflow task with a guaranteed outcome ───────────────────────────
const outcome = await agentic.task({
  agent: {
    model: "qwen/qwen3.7-max",
    system: "You are a bank task worker.",
    tools: { get_account },
  },
  prompt: "Look up ACC-1001's balance for its authenticated owner and submit it.",
  deliverable: z.object({ accountId: z.string(), balance: z.number() }),
});
// outcome.status: "submitted" (typed deliverable) | "cancelled" (model's
// escape hatch, with reason) | "failed" (bounded retries exhausted)

Every session — chats, workflows, one-shots — shares the same ledger, so all of it is resumable, auditable, and cost-tracked. Observability is one hook:

createAgentic({ onEvent: (e) => log(e) })
// run-start · step · retry · compaction · poke · run-end

À-la-carte helpers

Everything the harness is built from is exported for use with plain streamText/generateText:

Helper	What it does
createOpenRouter	drop-in provider factory with usage accounting on
logStream	pretty-print a full stream with live token/cost accounting
withRetries(fn)	retry any model call on transient failures, fail fast on deterministic ones
classifyFailure(err)	transient | context-overflow | fatal (+ Retry-After)
createResilientFetch	header + SSE-idle stall detection for hung connections
sanitizeConversation	heal interrupted/malformed tool-call transcripts before replay
guardToolResultSizes	cap tool results so one result can't blow the context window
extractStepUsage	per-step tokens + BYOK-reconciled cost from provider metadata
getContextWindow	a model's context length from OpenRouter, memoized

Local playground

playground/mvp/ has runnable proof demos (bring an OPENROUTER_API_KEY in .env):

npx tsx playground/mvp/demo-task.ts        # schema self-heal + guaranteed outcome
npx tsx playground/mvp/demo-chaos.ts       # injected 500s + severed SSE mid-run
npx tsx playground/mvp/demo-restart.ts     # SIGKILL mid-run → resume in new process
npx tsx playground/mvp/demo-compaction.ts  # memory survives two compactions
npx tsx playground/mvp/before-after/before.ts  # the plumbing you'd write by hand
npx tsx playground/mvp/before-after/after.ts   # the same workflow on the harness

Development

npm test          # vitest
npm run typecheck
npm run build     # tsup → dist/

License

MIT © Merkie