Claude Sonnet 5.5 (effort max · thinking on) on Effort dial sweep on one well-specified feature
AClaude Sonnet 5.5max · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-17 · by @bobsiopener
- Estimated cost
- $3.09
- Wall time
- 1.2h
- 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-sonnet-5.5: $3.08812. 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
- $3.09
- Wall time
- 1.2h
- Human step-ins
- 0
- Turns
- 43
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort max · thinking on | 4,475,482 | 183,751 | $3.09 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: Claude Sonnet 5.5 (anthropic/claude-sonnet-5.5, effort max · 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
[
{
"duration_api_ms": 1398301,
"stop_reason": "end_turn",
"session_id": "[REDACTED]",
"total_cost_usd": 3.0881199000000006,
"usage": {
"input_tokens": 58,
"cache_creation_input_tokens": 205885,
"cache_read_input_tokens": 4269539,
"output_tokens": 183751,
"output_tokens_details": {
"thinking_tokens": 148610
},
"server_tool_use": {
"web_search_requests": 0,
"web_fetch_requests": 0
},
"service_tier": "standard",
"cache_creation": {
"ephemeral_1h_input_tokens": 205885,
"ephemeral_5m_input_tokens": 0
},
"inference_geo": "global",
"iterations": [
{
"input_tokens": 2,
"output_tokens": 1992,
"cache_read_input_tokens": 213292,
"cache_creation_input_tokens": 5132,
"cache_creation": {
"ephemeral_5m_input_tokens": 0,
"ephemeral_1h_input_tokens": 5132
},
"type": "message"
}
],
"speed": "standard",
"fallback_credit": null
},
"modelUsage": {
"claude-sonnet-5-5": {
"inputTokens": 58,
"outputTokens": 183751,
"cacheReadInputTokens": 4269539,
"cacheCreationInputTokens": 205885,
"webSearchRequests": 0,
"costUSD": 3.0881199000000006,
"contextWindow": 1000000,
"maxOutputTokens": 128000,
"thinkingTokens": 148610,
"canonicalModel": "claude-sonnet-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
},
"started_in_background": 0,
"max_depth": 0,
"spawned_by_subagents": 0,
"completed": 0,
"failed": 0,
"killed": {
"parent": 0,
"user": 0,
"system": 0
},
"refused": {
"depth_limit": 0,
"concurrency_limit": 0,
"budget": 0
},
"by_type": {}
},
"safety_stops": 0,
"is_error": false,
"num_turns": 43,
"subtype": "success",
"api_error_status": null,
"result": "API-88 is done: `createRateLimiter` is in `src/middleware/rateLimit.js`, and `createApp({ rateLimit })` applies it to every `/notes` route but not `/health`. All 40 tests pass (the 4 existing plus 36 new) and `npm run lint` is clean. The changes are uncommitted in the working tree.\n\nI also ran the new tests five times, plus six runs under heavy CPU load, with no failures. I checked the wire format with `curl` against a real listening server. I also broke the implementation in 27 deliberate ways, and the suite now catches all of them.\n\n**How it works**\n- **Atomicity:** each check runs as one Lua script in Redis, so concurrent requests, including ones to different app instances, never get more than `capacity` tokens. In my tests, 60 concurrent requests against a capacity of 10 admitted exactly 10.\n- **Clock:** the script uses Redis `TIME`, not the app host's clock, so instances with skewed clocks agree on refill.\n- **TTL:** each key lives `capacity / refillPerSec`, the time an empty bucket takes to fill. An expired key and a full bucket are the same thing.\n- **Fail open:** this covers Redis errors, an unreachable server, a closed client and a server that never answers.\n\n**Decisions to review**\n- **`timeoutMs` option (my addition, default 500 ms):** I checked that an ioredis client with default settings hangs indefinitely when Redis is down or silent. A plain `try/catch` would have hung requests instead of letting them through, so the middleware has its own deadline. Even 4000 simultaneous requests against a healthy Redis never tripped it.\n- **Bad config throws at startup:** a missing `redis`, a non-integer `capacity` or a non-positive `refillPerSec` throws when the limiter is created. A `keyFn` that throws goes to the error handler (500) instead of failing open, since that's an app bug, not an outage.\n- **Float-noise bug found and fixed:** a naive `Retry-After` calculation reports 8 s instead of 7 s for a refill of 1/7 per second, because of floating-point noise. The script guards against this, and a test pins it.\n\n**Left for you**\n1. **`src/server.js` is unchanged, so the limiter is not active in production yet.** The ticket gives no production limits. Turning it on is one line: `createApp({ trustProxy: \u2026, rateLimit: { redis, capacity, refillPerSec } })`. Today it passes `{ redis }` at the top level, which `createApp` ignores. Set `trustProxy` if you're behind a proxy, or every client shares one bucket.\n2. **The limiter runs after `express.json()`.** A request with a malformed JSON body gets its 400 without using a token. Moving the limiter earlier would reorder the existing middleware, so the custom `middleware` option would stop seeing parsed bodies, and `keyFn` couldn't use identity those hooks set. I left the order alone and documented it in the README.\n3. **Test internals:** some tests write the `tokens` and `ts` hash fields directly to set up time-dependent cases without sleeping. They need updating if the storage layout ever changes. They also run `SCRIPT FLUSH` on the shared Redis, which clients recover from automatically.\n\nThe README has a new Rate limiting section covering the options, headers and these points.",
"ttft_ms": 1422,
"type": "result",
"duration_ms": 1876110,
"uuid": "[REDACTED]",
"ttft_stream_ms": 1327,
"time_to_request_ms": 286,
"first_content_frame_ms": 1327,
"queued_turn_count": 0,
"result_index": 0
}
]