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[rig-decomposition-bench] Daily rig decomposition benchmark — 2026-10-15 — no result (task picker failed)

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3/5
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半天
新手友好度
20/100
Issue 类型
缺陷
描述清晰度
基本清楚
活跃度
活跃
领域
tooling

调研方向

The run stops at the if (!task) early return in the workflow body, after the pickTask agent (maxTurns 2) returns null. The typecheck errors come from the skill's rig.ts, which lacks @types/node in its directory. Start by running --typecheck on rig.ts and checking whether the picker failure is related. Done means the typecheck passes and the benchmark reaches grading in one run.

由索引模型根据 Issue 内容生成。

描述

ai-agent automation

Result: benchmark did not complete

The task-picker agent (small, repair(), maxTurns: 2) returned null, so the workflow returned early. No task was chosen, and the single-call, decomposition and grading phases never ran. The program was run exactly once, as required.

Captured stdout: {"error":"task picker returned null"}
Captured stderr: empty

Before the run, --typecheck reported errors only in the skill's own rig.ts (for example, Cannot find name 'process' and Cannot find module 'node:path'). The cause is that @types/node is not installed in the skill directory. None were in the benchmark program.

Timing comparison
Single-call (ms) Decomposed (ms) Decomposed status
not run not run not run
Decomposition attempts

None, because the task was never picked.

Grading

Not run, so there are no scores, no winner and no rationale.

Single-call solution, decomposed program source and decomposed solution

None exist. No data was produced.

Benchmark program (Step 1)
import { agent, workflow, repair, configureAgent, copilotEngine, s } from "rig";

configureAgent(copilotEngine());

const DEADLINE = Date.now() + 25 * 60_000;
const left = () => DEADLINE - Date.now();

type RunResult = { status: "passed" | "failed" | "skipped"; stdout: string; stderr: string };

const cp = (globalThis as any).process.getBuiltinModule("node:child_process");

function runRig(source: string, flag: "--typecheck" | "--server", maxMs: number): Promise<RunResult> {
  const budget = Math.min(maxMs, left());
  if (budget < 5_000) return Promise.resolve({ status: "skipped", stdout: "", stderr: "time budget exhausted" });
  return new Promise((resolve) => {
    const child = cp.spawn("node", ["rig.ts", flag], { cwd: (globalThis as any).process.cwd(), stdio: ["pipe", "pipe", "pipe"] });
    let out = "";
    let err = "";
    let timedOut = false;
    const timer = setTimeout(() => { timedOut = true; child.kill("SIGKILL"); }, budget);
    child.stdout.on("data", (d: any) => { out += String(d); });
    child.stderr.on("data", (d: any) => { err += String(d); });
    child.on("error", (e: any) => { clearTimeout(timer); resolve({ status: "failed", stdout: out, stderr: err + String(e) }); });
    child.on("close", (code: number | null) => {
      clearTimeout(timer);
      if (timedOut) err += `\nTimed out after ${budget} ms`;
      resolve({ status: code === 0 && !timedOut ? "passed" : "failed", stdout: out, stderr: err });
    });
    child.stdin.on("error", () => {});
    child.stdin.end(source);
  });
}

// Agent role: pick a concrete benchmark task
const pickTask = agent({
  model: "small",
  maxTurns: 2,
  addons: repair(),
  instructions:
    "Pick one concrete, complicated task a person or team might face in a single day that would naturally benefit from being split across sub-agents running different models: multi-source research and synthesis, a multi-file coding task with design/implementation/review phases, a structured report combining several independent analyses, or a multi-step data transformation pipeline. It must be self-contained (no external files or live web) and gradable. Vary the domain; today's seed: " +
    String(Date.now() % 100000) +
    ". Return a title, a domain, a description, and 3-6 concrete checkable success criteria.",
  output: s.object({
    title: s.string,
    domain: s.string,
    description: s.string,
    criteria: s.array(s.string),
  }),
});

// Agent role: solve the whole task in one call
const solveSingle = agent({
  model: "medium",
  maxTurns: 1,
  instructions: "Solve the whole task yourself in one response, addressing every success criterion. No delegation, no tools. Return the complete solution.",
  output: s.string,
});

// Agent role: write the decomposed rig program
const writeProgram = agent({
  model: "medium",
  maxTurns: 1,
  instructions: "You write self-contained rig TypeScript programs. Return only the full TypeScript source, no commentary (a single ```ts fence is fine).",
  output: s.string,
});

// Agent role: fix or generate the rig program
const fixProgram = agent({
  model: "medium",
  maxTurns: 1,
  instructions: "You fix or generate self-contained rig TypeScript programs. Return only the full TypeScript source, no commentary (a single ```ts fence is fine).",
  output: s.string,
});

// Agent role: grade both solutions
const grader = agent({
  model: "large",
  maxTurns: 1,
  instructions:
    "Score each solution 0-10 on how completely and correctly it satisfies the success criteria. Judge only on correctness and completeness of content — not length and not which approach produced it. Pick a winner (single-call, decomposed, or tie) and explain the comparison.",
  output: s.object({
    singleScore: s.number,
    decomposedScore: s.number,
    winner: s.enum("single-call", "decomposed", "tie"),
    rationale: s.string,
  }),
});

const SKELETON = `import { agent, workflow, s } from "rig";

// Agent role: <role>
const analyze = agent({ model: "small", instructions: "...", output: s.string });

// Workflow role: combines the agents' outputs into the final solution
export default workflow({
  meta: { name: "decomposed-solution", description: "..." },
  body: async ({ call }) => {
    const analysis = await call(analyze, "...");
    return { solution: analysis ?? "" };
  },
});`;

const CONTRACT = `Rules: import only from "rig". Use at least two agents (the skeleton is abridged to one), each preceded by a "// Agent role: ..." comment, each with model "small" for simple sub-steps and "medium" or "large" for harder ones. Coordinate them so the final answer combines their outputs. The root takes no required input and is exported with \`export default\` without being invoked. A workflow() spec accepts only meta, an optional input, and body; it has no output or execute field — the final { solution } object is what body returns. An agent() root instead declares output: s.object({ solution: s.string }). Use s.string for every agent whose result is source text or free-form solution; do not make agents re-emit large solutions inside object wrappers. Do not use console.log.
Required shape:
${SKELETON}`;

function stripFence(src: string | null): string {
  const t = (src ?? "").trim();
  const m = t.match(/```(?:ts|typescript|rig)?\n([\s\S]*?)```/);
  return (m ? m[1] : t).trim();
}

type Attempt = {
  attempt: number;
  generation: string;
  typecheck: string;
  execute: string;
  error: string;
  note: string;
};

export default workflow({
  meta: { name: "rig-decomposition-bench", description: "Benchmarks single-call vs decomposed solving" },
  body: async ({ call }) => {
    const task = await call(pickTask, "Pick the task.");
    if (!task) return { error: "task picker returned null" };
    const taskText = `Title: ${task.title}\nDomain: ${task.domain}\nDescription: ${task.description}\nSuccess criteria:\n${task.criteria.map((c: string) => `- ${c}`).join("\n")}`;

    const t0 = Date.now();
    const single = (await call(solveSingle, taskText)) ?? "";
    const singleMs = Date.now() - t0;

    const t1 = Date.now();
    const attempts: Attempt[] = [];
    let source = "";
    let solution = "";
    let status: "pass" | "fail" = "fail";
    let lastError = "";
    let lastSource = "";
    for (let i = 1; i <= 2; i++) {
      if (left() < 4 * 60_000) break;
      let raw: string | null;
      if (i === 1) {
        raw = await call(writeProgram, `Write a rig program that solves this task by decomposing it across multiple agents.\n\n${taskText}\n\n${CONTRACT}`);
      } else if (lastSource) {
        raw = await call(fixProgram, `Fix this rig program precisely according to the error, preserving what already worked.\n\nTask:\n${taskText}\n\nSource:\n${lastSource}\n\nExact error:\n${lastError}\n\n${CONTRACT}`);
      } else {
        raw = await call(fixProgram, `There is no source to fix: the previous attempt produced nothing. Generate the complete program from scratch.\n\nTask:\n${taskText}\n\n${CONTRACT}`);
      }
      const src = stripFence(raw);
      const rec: Attempt = { attempt: i, generation: src ? "non-empty" : "empty", typecheck: "skipped", execute: "skipped", error: "", note: "" };
      attempts.push(rec);
      if (!src) {
        lastError = "writer returned empty source";
        rec.error = lastError;
        continue;
      }
      lastSource = src;
      source = src;
      const tc = await runRig(src, "--typecheck", 2 * 60_000);
      rec.typecheck = tc.status;
      if (tc.status !== "passed") {
        lastError = `typecheck:\n${tc.stdout}\n${tc.stderr}`.trim();
        rec.error = lastError;
        rec.note = i < 2 ? "Passed source and typecheck error to fixer" : "";
        continue;
      }
      const ex = await runRig(src, "--server", 5 * 60_000);
      rec.execute = ex.status;
      if (ex.status !== "passed") {
        lastError = `execute:\n${ex.stdout.slice(-3000)}\n${ex.stderr.slice(-6000)}`.trim();
        rec.error = lastError;
        rec.note = i < 2 ? "Passed source and execute error to fixer" : "";
        continue;
      }
      try {
        const parsed = JSON.parse(ex.stdout.trim());
        solution = typeof parsed === "string" ? parsed : String(parsed?.solution ?? "");
      } catch {
        solution = ex.stdout.trim();
      }
      if (solution.trim()) {
        status = "pass";
        break;
      }
      lastError = "execution produced empty solution\n" + ex.stdout;
      rec.error = lastError;
    }
    const decomposedMs = Date.now() - t1;

    const decomposedForGrade = solution.trim() ? solution : "(decomposition produced no solution)";
    const grade = await call(
      grader,
      `${taskText}\n\n=== SOLUTION A (single-call) ===\n${single || "(empty)"}\n\n=== SOLUTION B (decomposed) ===\n${decomposedForGrade}`,
    );

    return { task, singleMs, decomposedMs, singleSolution: single, decomposedSolution: solution, attempts, status, grade, decomposedSource: source };
  },
});

Verdict: no winner. The task picker returned null, so no comparison was possible.

Generated by Daily Rig Decomposition Benchmark · copilot · auto · 26.9 AIC · ⌖ 0.717 AIC · ⊞ 9.9K · ◷

  • expires on Oct 22, 2026, 1:08 PM UTC
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