Claude Sonnet 5.5 (effort low · thinking on) on Effort dial sweep on one well-specified feature

AClaude Sonnet 5.5low · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-16 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.11
Wall time: 45s
Human step-ins: 0
Outcome: Pass

Compare with other models on this task →

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: $0.109244. 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: $0.11
Wall time: 45s
Human step-ins: 0
Turns: 4

Model usage
Model	Input tok	Output tok	Cost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort low · thinking on	88,348	5,205	$0.11

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 low · 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.

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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": 35804,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.10924439999999999,
  "usage": {
   "input_tokens": 8,
   "cache_creation_input_tokens": 12396,
   "cache_read_input_tokens": 75944,
   "output_tokens": 5205,
   "output_tokens_details": {
    "thinking_tokens": 282
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 12396,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 745,
     "cache_read_input_tokens": 24750,
     "cache_creation_input_tokens": 185,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 185
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-sonnet-5-5": {
    "inputTokens": 8,
    "outputTokens": 5205,
    "cacheReadInputTokens": 75944,
    "cacheCreationInputTokens": 12396,
    "webSearchRequests": 0,
    "costUSD": 0.10924439999999999,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 282,
    "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": 4,
  "subtype": "success",
  "api_error_status": null,
  "result": "The rate limiter is in. All 16 tests pass (the 4 existing ones plus 12 new ones) and `npm run lint` is clean. I haven't committed anything.\n\n- **Limiter (`src/middleware/rateLimit.js`):** `createRateLimiter(options)` returns the middleware. Redis runs the whole check-and-consume as one Lua script, so concurrent requests can't over-spend a bucket.\n- **Clock:** the script uses Redis's own clock, so instances with skewed local clocks still share the same limits.\n- **Headers and 429:** a passing request gets `X-RateLimit-Limit` and `X-RateLimit-Remaining`. An empty bucket gets a 429 with `{\"error\":\"rate_limited\"}`, `X-RateLimit-Remaining: 0` and `Retry-After` in whole seconds, rounded up, minimum 1.\n- **TTL:** each bucket key expires after the time it would take to refill from empty, plus one second.\n- **Fail-open:** any Redis error lets the request through.\n- **Wiring (`src/app.js`):** `createApp({ rateLimit: {...} })` applies the limiter to `/notes` only, not `/health`. Without that option nothing changes.\n- **Tests (`test/rateLimit.test.js`):** the new tests run against the real Redis. They cover:\n  - the capacity sequence, refill over time, and `Retry-After` rounding\n  - separate buckets per key, the default `req.ip` key, and prefix with TTL\n  - 40 concurrent requests across two clients sharing one Redis, with exactly 10 allowed\n  - fail-open on an unreachable Redis and on a command error, and recovery after a script cache flush\n  - option validation and the `createApp` wiring\n\n**Option validation (my addition):** it throws a `TypeError` for a missing `redis`, a `capacity` that isn't a positive integer, or a `refillPerSec` that isn't greater than 0. A `refillPerSec` of 0 is rejected because a bucket that never refills would have no sensible TTL.\n\n**Test caveat:** the tests call `flushdb()` on the database `REDIS_URL` points to, which is fine for the scratch db 0 you described.",
  "ttft_ms": 2092,
  "type": "result",
  "duration_ms": 44774,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1005,
  "time_to_request_ms": 236,
  "first_content_frame_ms": 1005,
  "queued_turn_count": 0,
  "result_index": 0
 }
]