Claude Opus 5.5 (effort xhigh · thinking on) on Effort dial sweep on one well-specified feature
AClaude Opus 5.5xhigh · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-16 · by @bobsiopener
- Estimated cost
- $2.24
- Wall time
- 5.0h
- Human step-ins
- 0
- Outcome
- Pass
Compare with other models on this task →
Summary
Exact prompt
You are working in the notes-api repository (Express 4, Node 20, node:test + supertest, ESLint). A Redis server is running for you at the URL in the REDIS_URL environment variable (db 0 is scratch space you may flush). Ticket API-88: Add a rate-limiter middleware. Create src/middleware/rateLimit.js exporting createRateLimiter(options) that returns Express middleware implementing a per-key token bucket stored in Redis, so that several app instances sharing one Redis share the same limits. Options: - redis: an ioredis client (required) - capacity: bucket size (max burst), integer - refillPerSec: tokens added per second (may be fractional) - keyFn(req): returns the bucket key; default is req.ip - prefix: Redis key prefix, default 'rl:' Behaviour: - Each request consumes one token. If a token is available, call next() and set X-RateLimit-Limit (capacity) and X-RateLimit-Remaining (tokens left, integer, after this request). - If the bucket is empty, respond 429 with JSON {"error":"rate_limited"}, a Retry-After header (whole seconds, rounded up, at least 1) and X-RateLimit-Remaining: 0. Do not call next(). - The check-and-consume must be atomic under concurrent requests, including across app instances. - Bucket keys must not live forever in Redis: give them a TTL. - If Redis fails (error or unavailable), fail open: let the request through and do not crash. Wire it into the app so that createApp({ rateLimit: { redis, capacity, refillPerSec, ... } }) applies the limiter to all /notes routes (not /health). Add thorough tests (at least 8), keep the existing tests passing, and make sure `npm run lint` is clean.
The same feature ticket, a Redis-backed token-bucket rate limiter for an Express API, run at a range of reasoning-effort levels on models of different sizes. Nine hidden acceptance tests check burst limits, refill, atomicity under concurrency, sharing across app instances, key TTLs and fail-open behaviour, alongside lint and the agent's own tests. It shows what extra effort buys in tokens, cost and quality. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).
Success criteria: All provided acceptance tests pass; agent-written tests ≥ 8; no lint errors.
Setup notes: Synthetic Express 4 notes API (batch2/p02/repo) with a local redis-server 7 on the box. Same prompt for every run; only --model/--effort differ. Scored with 9 hidden acceptance tests (batch2/p02/hidden/acceptance.test.js, run after the agent finished), the agent's own test count (test()/it() calls outside the original notes tests), npm test and eslint. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Claude Code's own reported cost for claude-opus-5.5: $2.237501. Score: 9/9 acceptance. Cost is an ESTIMATE: measured tokens x pricing.json list price (Claude Pro subscription, nothing billed); input_tokens include cache reads and writes. Single run. Comparison on this use case: the same ticket at every Claude Code effort level (low, medium, high, xhigh, max) for Opus 5.5 and Sonnet 5.5, plus Haiku 5.5 at the default effort.
Estimated cost List-price estimate; not actually billed.
Metrics
- Estimated cost
- $2.24
- Wall time
- 5.0h
- Human step-ins
- 0
- Turns
- 19
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| AClaude Opus 5.5anthropic/claude-opus-5.5effort xhigh · thinking on | 1,058,194 | 60,917 | $2.24 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: Claude Opus 5.5 (anthropic/claude-opus-5.5, effort xhigh · thinking on) via
Claude Code 2.1.299 (headless -p), cloud. - It counts as a success only if it meets every success criterion: All provided acceptance tests pass; agent-written tests ≥ 8; no lint errors.
- Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.
How runs are scored: Methodology.
Was this useful?
Automated checks
Trust 80% comes from these checks (how Trust % works).
- Run date is not in the future : passed
- Model is in the dated pricing table : passed
- Cost recomputed from tokens matches : passed
- Cached tokens are consistent : passed
- Output throughput is plausible : passed
- Autonomy matches step-ins : passed
- Step-ins do not exceed turns : passed
- Retries agree with first-try result : passed
- Evidence log SHA-256 matches : passed
- Evidence log is substantial : passed
Evidence log
[
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"stop_reason": "end_turn",
"session_id": "[REDACTED]",
"total_cost_usd": 2.237501,
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"cache_creation_input_tokens": 103509,
"cache_read_input_tokens": 954645,
"output_tokens": 60917,
"output_tokens_details": {
"thinking_tokens": 45510
},
"server_tool_use": {
"web_search_requests": 0,
"web_fetch_requests": 0
},
"service_tier": "standard",
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"inference_geo": "global",
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{
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"cache_creation": {
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},
"type": "message"
}
],
"speed": "standard",
"fallback_credit": null
},
"modelUsage": {
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"inputTokens": 40,
"outputTokens": 60917,
"cacheReadInputTokens": 954645,
"cacheCreationInputTokens": 103509,
"webSearchRequests": 0,
"costUSD": 2.237501,
"contextWindow": 1000000,
"maxOutputTokens": 128000,
"thinkingTokens": 45510,
"canonicalModel": "claude-opus-5-5",
"provider": "firstParty",
"costBasis": "list"
}
},
"permission_denials": [],
"terminal_reason": "completed",
"fast_mode_state": "off",
"fast_mode_disabled_reason": "sdk_opt_in_required",
"subagent_stats": {
"spawned": 0,
"requested": {
"background": 0,
"foreground": 0,
"unset": 0
},
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"refused": {
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"by_type": {}
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"safety_stops": 0,
"is_error": false,
"num_turns": 19,
"subtype": "success",
"api_error_status": null,
"result": "The rate limiter for API-88 is in place: `/notes` routes are limited per key, `/health` is not, and all 19 tests (4 existing, 15 new) pass with `npm run lint` clean. Nothing is committed yet.\n\n**What's there**\n- **`src/middleware/rateLimit.js`** exports `createRateLimiter(options)`. One Lua script does the whole check-and-consume (refill, consume one token, save), and Redis runs scripts atomically, so limits hold under concurrency and across app instances. The script uses Redis's own clock, so clock differences between app servers don't change the limits.\n- **Expiry:** each bucket key expires when the bucket would be full again. A missing key means a full bucket, so expiry never changes behaviour. Denied requests don't write to Redis at all.\n- **Fail open:** Redis errors let the request through. I also added a timeout (`timeoutMs`, default 250ms). With default ioredis settings, a call made while Redis is down waits about 10s before failing, or never fails if Redis accepts the connection but doesn't answer. Without the timeout, \"fail open\" would really mean slow or stuck requests.\n- **Script reloading:** if Redis loses its script cache (restart, failover), the middleware reloads the script. Otherwise every request would quietly fail open from then on.\n- **`src/app.js`** applies the limiter to `/notes` when `options.rateLimit` is given. Bad options (missing client, `capacity` 0, `refillPerSec` 0, etc.) throw an error when `createApp` is called.\n- **`README.md`** documents the options and behaviour.\n\n**Testing**\n- The tests run against the real Redis. Each run uses its own key prefix and deletes its keys afterwards; no keys were left over.\n- They cover: header values; 429 body, headers and the route not being reached; `Retry-After` rounding (2.5s \u2192 `3`, 0.5s \u2192 `1`); refill keeping fractional tokens; the capacity cap; 40 concurrent requests on one instance and split across two Redis connections (exactly 10 allowed); per-IP and custom keys; `/health` not limited; expiry; Redis errors; Redis not answering; and option checks.\n- To check the tests actually catch bugs, I broke the code 12 different ways in a scratch copy, and each break made at least one test fail. The most important one: a read-then-write version that isn't atomic fails both concurrency tests. That process also exposed two weak tests, which I fixed.\n- The timing-based tests passed 11 times in a row normally and 6 more times under CPU load, 3 of them with every core saturated.\n\n**Decisions for you**\n1. **Nothing turns it on in production.** `src/server.js` doesn't pass `rateLimit`, because the actual limits are a product decision. Once you pick numbers, wiring them in from environment variables is a few lines.\n2. **Behind a load balancer**, set `trustProxy`. Otherwise `req.ip` is the proxy's address and every client shares one bucket.\n3. **During a Redis outage**, the default `onError` logs one line per request let through. If that's too much log volume at your traffic, pass a quieter `onError`.\n4. **If a custom `keyFn` throws**, the request goes to the error handler as a 500 rather than failing open. I treated that as a code bug rather than a Redis failure.\n\nWant me to commit this on a branch and open a PR against `main`?",
"ttft_ms": 1724,
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"uuid": "[REDACTED]",
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]