feat: multi-provider model benchmark (boil the ocean)

Adds the full spec Codex asked for: real provider adapters with auth
detection, normalized RunResult, pricing tables, tool compatibility
maps, parallel execution with error isolation, and table/JSON/markdown
output. Judge stays on Anthropic SDK as the single stable source of
quality scoring, gated behind --judge.

Codex flagged the original plan as massively under-scoped — the
existing runner is Claude-only and the judge is Anthropic-only. You
can't benchmark GPT or Gemini without real provider infrastructure.
This commit ships it.

New architecture:

  test/helpers/providers/types.ts       ProviderAdapter interface
  test/helpers/providers/claude.ts      wraps `claude -p --output-format json`
  test/helpers/providers/gpt.ts         wraps `codex exec --json`
  test/helpers/providers/gemini.ts      wraps `gemini -p --output-format stream-json --yolo`
  test/helpers/pricing.ts               per-model USD cost tables (quarterly)
  test/helpers/tool-map.ts              which tools each CLI exposes
  test/helpers/benchmark-runner.ts      orchestrator (Promise.allSettled)
  test/helpers/benchmark-judge.ts       Anthropic SDK quality scorer
  bin/gstack-model-benchmark            CLI entry
  test/benchmark-runner.test.ts         9 unit tests (cost math, formatters, tool-map)

Per-provider error isolation:
  - auth → record reason, don't abort batch
  - timeout → record reason, don't abort batch
  - rate_limit → record reason, don't abort batch
  - binary_missing → record in available() check, skip if --skip-unavailable

Pricing correction: cached input tokens are disjoint from uncached
input tokens (Anthropic/OpenAI report them separately). Original
math subtracted them, producing negative costs. Now adds cached at
the 10% discount alongside the full uncached input cost.

CLI:
  gstack-model-benchmark --prompt "..." --models claude,gpt,gemini
  gstack-model-benchmark ./prompt.txt --output json --judge
  gstack-model-benchmark ./prompt.txt --models claude --timeout-ms 60000

Output formats: table (default), json, markdown. Each shows model,
latency, in→out tokens, cost, quality (when --judge used), tool calls,
and any errors.

Known limitations for v1:
- Claude adapter approximates toolCalls as num_turns (stream-json
  would give exact counts; v2 can upgrade).
- Live E2E tests (test/providers.e2e.test.ts) not included — they
  require CI secrets for all three providers. Unit tests cover the
  shape and math.
- Provider CLIs sometimes return non-JSON error text to stdout; the
  parsers fall back to treating raw output as plain text in that case.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

test/helpers/providers/gpt.ts

@@ -0,0 +1,122 @@
+import type { ProviderAdapter, RunOpts, RunResult, AvailabilityCheck } from './types';
+import { estimateCostUsd } from '../pricing';
+import { execFileSync, spawnSync } from 'child_process';
+import * as fs from 'fs';
+import * as path from 'path';
+import * as os from 'os';
+
+/**
+ * GPT adapter — wraps the OpenAI `codex` CLI (codex exec with --json output).
+ *
+ * Codex uses ~/.codex/ for auth (not OPENAI_API_KEY). The --json flag emits
+ * JSONL events; we parse `turn.completed` for usage and `agent_message` / etc.
+ * for output aggregation.
+ */
+export class GptAdapter implements ProviderAdapter {
+  readonly name = 'gpt';
+  readonly family = 'gpt' as const;
+
+  async available(): Promise<AvailabilityCheck> {
+    const res = spawnSync('sh', ['-c', 'command -v codex'], { timeout: 2000 });
+    if (res.status !== 0) {
+      return { ok: false, reason: 'codex CLI not found on PATH. Install: npm i -g @openai/codex' };
+    }
+    // Auth sniff: ~/.codex/ should contain auth state after `codex login`
+    const codexDir = path.join(os.homedir(), '.codex');
+    if (!fs.existsSync(codexDir)) {
+      return { ok: false, reason: 'No ~/.codex/ found. Run `codex login` to authenticate via ChatGPT.' };
+    }
+    return { ok: true };
+  }
+
+  async run(opts: RunOpts): Promise<RunResult> {
+    const start = Date.now();
+    const args = ['exec', opts.prompt, '-C', opts.workdir, '-s', 'read-only', '--json'];
+    if (opts.model) args.push('-m', opts.model);
+    if (opts.extraArgs) args.push(...opts.extraArgs);
+
+    try {
+      const out = execFileSync('codex', args, {
+        cwd: opts.workdir,
+        timeout: opts.timeoutMs,
+        encoding: 'utf-8',
+        maxBuffer: 32 * 1024 * 1024,
+      });
+      const parsed = this.parseJsonl(out);
+      return {
+        output: parsed.output,
+        tokens: parsed.tokens,
+        durationMs: Date.now() - start,
+        toolCalls: parsed.toolCalls,
+        modelUsed: parsed.modelUsed || opts.model || 'gpt-5.4',
+      };
+    } catch (err: unknown) {
+      const durationMs = Date.now() - start;
+      const e = err as { code?: string; stderr?: Buffer; signal?: string; message?: string };
+      const stderr = e.stderr?.toString() ?? '';
+      if (e.signal === 'SIGTERM' || e.code === 'ETIMEDOUT') {
+        return this.emptyResult(durationMs, { code: 'timeout', reason: `exceeded ${opts.timeoutMs}ms` }, opts.model);
+      }
+      if (/unauthorized|auth|login/i.test(stderr)) {
+        return this.emptyResult(durationMs, { code: 'auth', reason: stderr.slice(0, 400) }, opts.model);
+      }
+      if (/rate[- ]?limit|429/i.test(stderr)) {
+        return this.emptyResult(durationMs, { code: 'rate_limit', reason: stderr.slice(0, 400) }, opts.model);
+      }
+      return this.emptyResult(durationMs, { code: 'unknown', reason: (e.message ?? stderr ?? 'unknown').slice(0, 400) }, opts.model);
+    }
+  }
+
+  estimateCost(tokens: { input: number; output: number; cached?: number }, model?: string): number {
+    return estimateCostUsd(tokens, model ?? 'gpt-5.4');
+  }
+
+  /**
+   * Parse codex exec --json JSONL stream.
+   * Key events:
+   *   - item.completed with item.type === 'agent_message' → text output
+   *   - item.completed with item.type === 'command_execution' → tool call
+   *   - turn.completed → usage.input_tokens, usage.output_tokens
+   *   - thread.started → session id (not used here)
+   */
+  private parseJsonl(raw: string): { output: string; tokens: { input: number; output: number }; toolCalls: number; modelUsed?: string } {
+    let output = '';
+    let input = 0;
+    let out = 0;
+    let toolCalls = 0;
+    let modelUsed: string | undefined;
+    for (const line of raw.split('\n')) {
+      const s = line.trim();
+      if (!s) continue;
+      try {
+        const obj = JSON.parse(s);
+        if (obj.type === 'item.completed' && obj.item) {
+          if (obj.item.type === 'agent_message' && typeof obj.item.text === 'string') {
+            output += (output ? '\n' : '') + obj.item.text;
+          } else if (obj.item.type === 'command_execution') {
+            toolCalls += 1;
+          }
+        } else if (obj.type === 'turn.completed') {
+          const u = obj.usage ?? {};
+          input += u.input_tokens ?? 0;
+          out += u.output_tokens ?? 0;
+          if (obj.model) modelUsed = obj.model;
+        }
+      } catch {
+        // skip malformed lines — codex stderr can leak in
+      }
+    }
+    return { output, tokens: { input, output: out }, toolCalls, modelUsed };
+  }
+
+  private emptyResult(durationMs: number, error: RunResult['error'], model?: string): RunResult {
+    return {
+      output: '',
+      tokens: { input: 0, output: 0 },
+      durationMs,
+      toolCalls: 0,
+      modelUsed: model ?? 'gpt-5.4',
+      error,
+    };
+  }
+}