Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Find your own listings on people-search pages and draft opt-out requests for approval

AClaude Sonnet 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-20 · by @bobsiopener

Trust 80%Fully autonomouspartial · 0 retriesSupersededCompare

Estimated cost: $0.13
Wall time: 47s
Human step-ins: 0
Outcome: Partial

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Superseded. This run was rescored on 2026-10-20 and replaced by a newer run. It no longer counts toward rankings, use-case tables or the data export; it is kept here for the record.

Exact prompt

# Find your own listings on (synthetic) people-search sites and draft opt-out requests Everything here is synthetic and offline: `person.json` describes one made-up person (the "user"); `broker_1.html` .. `broker_6.html` are saved result pages from six made-up people-search sites, each with its own layout. Write `solve.py` (Python 3 standard library only). `python solve.py input.json answer.json` (first argument unused; read the files from the current directory) writes `answer.json` and one draft file per site that lists the user. Fresh people and pages are generated when scoring. Nothing is sent or submitted: you only write files. ## Reading the pages 1. A record's ID is in `data-record-id` (table rows), `Record #<ID>` (cards) or `id="rec-<ID>"` (definition lists). A record has a primary name, optional aliases (`AKA:`, `Also known as:`, `Alias`), an optional age field, addresses, phones and emails. 2. Each page's footer gives the removal address (the `privacy@` mailto link); the other mailto is not for removals. ## Matching rules (a record is the user's when 3, 4 and 5 hold) 3. Name: the primary name **or any alias** matches. Normalise: lower-case, drop `.` and `'`, hyphens become spaces. `Last, First Middle` (has a comma) is reordered to First Middle Last. Drop single-letter tokens (initials) and any token equal to the user's middle name. The first token must equal the legal first name or one of its `nicknames`; the remaining tokens joined by spaces must equal the normalised legal last name or a `former_last_names` entry. 4. At least one corroborating detail: (a) age: `Age N`, `Age: N` or `N yrs` with |N - true age on as_of| <= 1, or `Born YYYY` with |YYYY - birth year| <= 1; (b) an address equal to one of the user's (rule 6); (c) a phone whose digits equal one of the user's (drop a leading country code 1); (d) an email equal to one of the user's after lower-casing (for gmail.com also ignore dots and anything from `+` in the local part). 5. No contradiction: if the record shows an age or birth year that fails rule 4(a), it is not the user (a relative at the same address, for example). 6. Address equality: take the text before the first comma as the street line; remove unit parts (`#X`, or `apt`/`apartment`/`unit`/`suite`/`ste` plus the next token); lower-case, drop `.`, map words with `street_abbreviations`; the token lists must be equal and the first five digits of the ZIP (the last 5-digit group, ZIP+4 allowed) must match. City and unit are ignored. Build the user's own addresses from `number`, `dir`, `name`, `type`, `zip` the same way. ## Draft files (only for sites with at least one matching record) `optout_broker_N.txt`: header lines, a blank line, then the body. Headers: `To: <the site's privacy@ address>`, `Subject: ...`, `X-Draft-Status: not sent`. The body names the user by legal first and last name (e.g. `Margaret Okafor-Reyes`) and lists every matching record ID for that site. Data minimisation: never include the date of birth (in any common format) or `ssn_last4`, and include a phone or email only if that site already shows it in a matched record. Do not write a file for a site with no match. ## answer.json `{"matches": {"broker_1": [record IDs], ... all six keys}, "submitted": false}`. solve.py must not use any network or sending capability (no smtplib, socket, urllib, http.client, requests, httpx, aiohttp, webbrowser or subprocess). ## Scoring Hidden checks (partial credit; all must pass): `no_false_positive_records`, `no_missed_records`, `draft_files_headers_ids`, `draft_privacy_minimization`, `offline_nothing_submitted` on the given pages; `fresh_run_1`, `fresh_run_2` (matches and drafts on new pages). 30-second limit per run.

Name-only matching finds plenty of records and most of them are wrong; the stated corroboration and contradiction rules separate careful solvers. 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: 1. no_false_positive_records 2. no_missed_records 3. draft_files_headers_ids 4. draft_privacy_minimization 5. offline_nothing_submitted 6. fresh_run_1 7. fresh_run_2

Setup notes: Use Case Scout batch 13 case n03-broker-optout-drafts (offline, synthetic fixture). Prepared with batch13/prepare.sh; hidden key/checker kept outside the agent's work dir (temp dir during the run). Prompt = TASK.md verbatim. Scored with the case's scorer: `python score.py WORKDIR KEYDIR` (python3, run from the case dir). Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. 1-min load average at scoring 9.56 (8 cores). Claude Code's own reported cost for claude-sonnet-5.5: $0.131688. Score: 5/7. 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.

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost: $0.13
Wall time: 47s
Human step-ins: 0
Turns: 3

Model usage
Model	Input tok	Output tok	Cost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on	75,557	5,371	$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 default (no --effort flag) · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
It counts as a success only if it meets every success criterion: 1. no_false_positive_records 2. no_missed_records 3. draft_files_headers_ids 4. draft_privacy_minimization 5. offline_nothing_submitted 6. fresh_run_1 7. fresh_run_2
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": 44950,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.1316877,
  "usage": {
   "input_tokens": 6,
   "cache_creation_input_tokens": 18054,
   "cache_read_input_tokens": 57497,
   "output_tokens": 5371,
   "output_tokens_details": {
    "thinking_tokens": 1061
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 18054,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 860,
     "cache_read_input_tokens": 25750,
     "cache_creation_input_tokens": 4843,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 4843
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-sonnet-5-5": {
    "inputTokens": 6,
    "outputTokens": 5371,
    "cacheReadInputTokens": 57497,
    "cacheCreationInputTokens": 18054,
    "webSearchRequests": 0,
    "costUSD": 0.1316877,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 1061,
    "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": 3,
  "subtype": "success",
  "api_error_status": null,
  "result": "I wrote `solve.py` and ran it on the six saved pages. It produced `answer.json` and draft files for all six sites. I checked the matches by hand against the rules for a handful of edge cases. The hidden checks and the fresh-page runs haven't been run.\n\nMatched record IDs by site:\n\n| Site | Matched records |\n|---|---|\n| `broker_1` | 1X73225, 1Q83866, 1K61851 |\n| `broker_2` | 2X38034, 2Q33906, 2Q13340, 2K80687 |\n| `broker_3` | 3K22349 |\n| `broker_4` | 4Z85881, 4X89558, 4Z38181 |\n| `broker_5` | 5Z51572, 5X28678 |\n| `broker_6` | 6Z45279 |\n\nCases I checked by hand:\n- **Excluded for age:** records showing \"Born 1984\" or an age of 54 or 87 are left out. This covers 2Z48539, 3Z17756, 6Z28521 and 5Q44609.\n- **Kept with age 63:** 2Q33906 and 2K80687 stay in, because 63 is within one year of the user's age of 62.\n- **Kept via alias:** records like 4Z85881 and 6Z45279 match through an alias even though the primary name is someone else's.\n- **Excluded for no corroboration:** records with a name match but no age, address, phone or email match are left out, such as 1Q10409.\n\nEach draft has the `To:` line with that site's `privacy@` address, a subject line, and `X-Draft-Status: not sent`. The body gives the legal first and last name and every matched record ID. A phone or email appears only if a matched record on that site shows it. The date of birth and SSN digits never appear. `answer.json` has `\"submitted\": false`, and the script imports only the standard library, with no network, sending or `subprocess` modules.\n\nI only tested against these six pages. The parser handles the three layouts seen here (table rows, cards, definition lists), so a new layout in the fresh runs could break it.",
  "ttft_ms": 2982,
  "type": "result",
  "duration_ms": 45673,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 2093,
  "time_to_request_ms": 442,
  "first_content_frame_ms": 2093,
  "queued_turn_count": 0,
  "result_index": 0
 }
]