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

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

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.13
Wall time: 50s
Human step-ins: 0
Outcome: Pass

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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: $0.129467. 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: $0.13
Wall time: 50s
Human step-ins: 0
Turns: 5

Model usage
Model	Input tok	Output tok	Cost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort medium · thinking on	110,849	6,482	$0.13

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 medium · 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

[
 {
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  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.129467,
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   "output_tokens": 6482,
   "output_tokens_details": {
    "thinking_tokens": 462
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 13729,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 751,
     "cache_read_input_tokens": 26043,
     "cache_creation_input_tokens": 225,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 225
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-sonnet-5-5": {
    "inputTokens": 10,
    "outputTokens": 6482,
    "cacheReadInputTokens": 97110,
    "cacheCreationInputTokens": 13729,
    "webSearchRequests": 0,
    "costUSD": 0.129467,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 462,
    "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,
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   "killed": {
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   "refused": {
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    "concurrency_limit": 0,
    "budget": 0
   },
   "by_type": {}
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  "safety_stops": 0,
  "is_error": false,
  "num_turns": 5,
  "subtype": "success",
  "api_error_status": null,
  "result": "The rate limiter is in. All 22 tests pass (the original ones plus 18 new) and `npm run lint` is clean. I haven't committed anything.\n\n- **Limiter:** `src/middleware/rateLimit.js` exports `createRateLimiter(options)`, a per-key token bucket stored in a Redis hash. The refill-and-consume step is one Lua script, so it is atomic across concurrent requests and across app instances sharing a Redis. The script reads the time from Redis, so clock differences between instances don't matter.\n- **Responses:**\n  - An allowed request calls `next()` and sets `X-RateLimit-Limit` and `X-RateLimit-Remaining`.\n  - A request on an empty bucket gets 429 with `{\"error\":\"rate_limited\"}`, `Retry-After` (whole seconds, rounded up, at least 1) and `X-RateLimit-Remaining: 0`.\n- **TTL:** bucket keys expire after the time it takes to refill from empty, plus 1 second.\n- **Fail open:** any Redis error lets the request through. I also added a `timeoutMs` option (default 1000 ms), not in the ticket. Without it, a hung Redis would stall requests instead of failing open.\n- **Validation:** it throws a `TypeError` if `redis` is missing, `capacity` isn't a positive integer, or `refillPerSec` isn't greater than 0. That goes beyond the spec.\n- **Wiring:** `createApp({ rateLimit: {...} })` applies the limiter to `/notes` only, and `/health` is unaffected. Without the option the app behaves as before.\n- **Tests:** `test/rateLimit.test.js` runs against the real Redis. It covers:\n  - capacity, headers and `Retry-After`;\n  - refill, including fractional rates;\n  - `keyFn`, prefix and TTL;\n  - 30 concurrent requests, and two clients on one Redis sharing a limit;\n  - fail-open on an error, an unreachable Redis, and a hung Redis;\n  - option validation and the `createApp` wiring.\n\nBecause the limiter falls back to `req.ip`, behind a proxy you need `trustProxy` set in `createApp`, or every client will share one bucket.",
  "ttft_ms": 2222,
  "type": "result",
  "duration_ms": 49745,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1140,
  "time_to_request_ms": 219,
  "first_content_frame_ms": 1140,
  "queued_turn_count": 0,
  "result_index": 0
 }
]