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

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

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.60
Wall time
3m
Human step-ins
0
Outcome
Pass

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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: $0.599135. 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
$0.60
Wall time
3m
Human step-ins
0
Turns
13
Model usage
ModelInput tokOutput tokCost
AClaude Opus 5.5anthropic/claude-opus-5.5effort high · thinking on233,04417,174$0.60

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Claude Opus 5.5 (anthropic/claude-opus-5.5, effort high · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
  3. It counts as a success only if it meets every success criterion: All provided acceptance tests pass; agent-written tests ≥ 8; no lint errors.
  4. 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

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Evidence log
[
 {
  "duration_api_ms": 146889,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.5991350000000001,
  "usage": {
   "input_tokens": 16,
   "cache_creation_input_tokens": 26793,
   "cache_read_input_tokens": 206235,
   "output_tokens": 17174,
   "output_tokens_details": {
    "thinking_tokens": 6064
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 26793,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 1116,
     "cache_read_input_tokens": 38534,
     "cache_creation_input_tokens": 405,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 405
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-opus-5-5": {
    "inputTokens": 16,
    "outputTokens": 17174,
    "cacheReadInputTokens": 206235,
    "cacheCreationInputTokens": 26793,
    "webSearchRequests": 0,
    "costUSD": 0.5991350000000001,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 6064,
    "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
   },
   "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": 13,
  "subtype": "success",
  "api_error_status": null,
  "result": "I've added the rate limiter for API-88. `npm test` passes all 26 tests (the 4 existing ones plus 22 new ones that run against the real Redis), five runs in a row, and `npm run lint` is clean. Nothing is committed.\n\n**What it does** (`src/middleware/rateLimit.js`)\n- **One atomic step in Redis:** a small Redis script refills the bucket, takes a token and saves the result in a single operation. That keeps it correct when many requests arrive at once, whether they hit one app instance or several.\n- **One shared clock:** the time comes from the Redis server rather than each app server, so instances whose clocks disagree still agree on how full a bucket is.\n- **Keys expire:** each bucket key's expiry is the time a full refill takes plus 1 second. An expired key and a full bucket mean the same thing, so this loses no information.\n- **Responses:** allowed requests get `X-RateLimit-Limit` and `X-RateLimit-Remaining`. Blocked requests get 429 with `{\"error\":\"rate_limited\"}`, `X-RateLimit-Remaining: 0` and `Retry-After` (whole seconds, rounded up, at least 1), and never reach the route.\n- **Fails open:** if Redis returns an error, throws, the client is closed, or Redis doesn't answer in time, the request goes through and the error is passed to `onError`. Bad options throw a `TypeError` when the app is created.\n\n**Two options the ticket didn't ask for:**\n- `timeoutMs` (default 500). By default ioredis holds commands in a queue while Redis is down and keeps retrying them, so without a timeout requests would hang rather than fail open.\n- `onError(err, req)`, which by default prints a warning.\n\n**Wiring** (`src/app.js`): `createApp({ rateLimit: {...} })` puts the limiter in front of the `/notes` routes only, so `/health` isn't limited. Without the option, the app behaves as before.\n\n**Tests** (`test/rateLimit.test.js`) cover:\n- burst, remaining count, 429 and `Retry-After` values, including fractional refill rates\n- refill over time, never refilling past capacity\n- 60 simultaneous requests letting exactly 10 through\n- three app instances on separate Redis connections sharing one limit\n- per-key buckets, the default IP key, key prefix and expiry\n- `/health` not being limited\n- recovery after Redis clears its stored scripts\n- failing open in five different failure cases, and option checks\n\n**Things to decide:**\n- `src/server.js` doesn't turn rate limiting on yet, because the ticket didn't say what limits production should use. Tell me the values (or which environment variables to read them from) and I'll add it.\n- The limiter runs after the app reads the request body, so `keyFn` can use anything earlier middleware sets, such as a logged-in user. The catch is that requests with broken JSON get their 400 error before the limiter runs, so they aren't counted.\n- With the default key, all clients behind a proxy share one bucket unless the app is created with `trustProxy` set.\n- If `keyFn` returns nothing, those requests all share one bucket named `undefined`. I chose this so leaving out a header can't be used to get around the limit.\n\nI also added a short \"Rate limiting\" section to the README.",
  "ttft_ms": 1678,
  "type": "result",
  "duration_ms": 171671,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1022,
  "time_to_request_ms": 233,
  "first_content_frame_ms": 1022,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

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