GPT-6.1 Sol (effort default (no reasoning-effort override) · thinking on) on Find your own listings on people-search pages and draft opt-out requests for approval
OGPT-6.1 Soldefault · thinking on · Codex CLI 0.163.0 (codex exec --json) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.08
- Wall time
- 1m
- Human step-ins
- 0
- Outcome
- Pass
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Summary
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. Headless, offline run on a reproducible fixture. Cost shown is a list-price API-equivalent estimate (run on a ChatGPT subscription, not billed).
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 batch13 case n03-broker-optout-drafts (offline fixture). Prepared with batch13/prepare.sh on the shared box; only TASK.md + starting files were copied to the agent machine, hidden key/tests stayed on the box. Prompt = TASK.md verbatim on stdin. Flags: --json -s workspace-write --skip-git-repo-check --ephemeral --ignore-user-config --ignore-rules -C <workdir>. Scored on the box with the scout's scorer: `python score.py WORKDIR KEYDIR`. Single run, no retries. User-level AGENTS.md (846 bytes, sha256 83ec4fe50da8) may have been in context; --ignore-user-config does not document excluding it. Serving model not confirmed: requested via -m; the event log does not echo the serving model id. Price source is secondary (pricing.json verification='secondary', https://www.actuia.com/en/news/ai-api-pricing-in-october-2026-050-to-50-for-output/), not an official OpenAI price page. Score: 7/7. Cost is an ESTIMATE: measured tokens x pricing.json list price (ChatGPT plan, nothing billed); input_tokens include cached reads; output_tokens include reasoning tokens. Tool calls 5 (2 failed, recovered). Single run.
Estimated cost List-price estimate; not actually billed.
Metrics
- Estimated cost
- $0.08
- Wall time
- 1m
- Human step-ins
- 0
- Turns
- 1
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| OGPT-6.1 Solopenai/gpt-6.1-soleffort default (no reasoning-effort override) · thinking on | 106,738 | 3,031 | $0.08 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: GPT-6.1 Sol (openai/gpt-6.1-sol, effort default (no reasoning-effort override) · thinking on) via
Codex CLI 0.163.0 (codex exec --json), cloud. - It counts as a success only if it meets every success criterion: 1. no_false_positive_records 2. no_missed_records 3. draft_files_headers_ids 4. draft_privacy_minimization 5. offline_nothing_submitted 6. fresh_run_1 7. fresh_run_2
- Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.
How runs are scored: Methodology.
Was this useful?
Automated checks
Trust 80% comes from these checks (how Trust % works).
- Run date is not in the future : passed
- Model is in the dated pricing table : passed
- Cost recomputed from tokens matches : passed
- Cached tokens are consistent : passed
- Output throughput is plausible : passed
- Autonomy matches step-ins : passed
- Step-ins do not exceed turns : passed
- Retries agree with first-try result : passed
- Evidence log SHA-256 matches : passed
- Evidence log is substantial : passed
Evidence log
{"type": "thread.started", "thread_id": "01a16413-3ffa-7b71-909a-b2ff9e99bf3d"}
{"type": "turn.started"}
{"type": "item.completed", "item": {"id": "item_0", "type": "agent_message", "text": "I\u2019ll inspect the sample data, then write and test an offline parser that matches records and creates the draft files."}}
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{"type": "item.completed", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc 'ls -la; cat person.json; for f in broker_*.html; do echo \"$f\"; head -c 14000 \"$f\"; done'", "aggregated_output": "total 40\ndrwxr-xr-x 6 bob bob 4096 Oct 22 10:45 .\ndrwxrwxr-x 3 bob bob 4096 Oct 22 10:45 ..\ndr-xr-xr-x 2 bob bob 40 Oct 22 10:45 .agents\ndr-xr-xr-x 2 bob bob 40 Oct 22 10:45 .aws\ndr-xr-xr-x 2 bob bob 40 Oct 22 10:45 .codex\ndr-xr-xr-x 2 bob bob 40 Oct 22 10:45 .git\n-rw-r--r-- 1 bob bob 3719 Oct 22 10:08 TASK.md\n-rw-r--r-- 1 bob bob 1658 Oct 22 10:08 broker_1.html\n-rw-r--r-- 1 bob bob 2557 Oct 22 10:08 broker_2.html\n-rw-r--r-- 1 bob bob 1561 Oct 22 10:08 broker_3.html\n-rw-r--r-- 1 bob bob 1576 Oct 22 10:08 broker_4.html\n-rw-r--r-- 1 bob bob 2519 Oct 22 10:08 broker_5.html\n-rw-r--r-- 1 bob bob 1229 Oct 22 10:08 broker_6.html\n-rw-r--r-- 1 bob bob 1112 Oct 22 10:08 person.json\n{\n \"legal_name\": {\n \"first\": \"Margaret\",\n \"middle\": \"Ann\",\n \"last\": \"Van Der Berg\"\n },\n \"former_last_names\": [\n \"Smith\"\n ],\n \"date_of_birth\": \"1964-08-19\",\n \"ssn_last4\": \"7048\",\n \"as_of\": \"2026-10-20\",\n \"addresses\": [\n {\n \"number\": \"5442\",\n \"dir\": \"West\",\n \"name\": \"Harbor\",\n \"type\": \"Road\",\n \"unit\": \"A\",\n \"city\": \"Boise\",\n \"state\": \"ID\",\n \"zip\": \"60121\"\n },\n {\n \"number\": \"71\",\n \"dir\": \"\",\n \"name\": \"Cedar\",\n \"type\": \"Court\",\n \"unit\": \"A\",\n \"city\": \"Albany\",\n \"state\": \"NY\",\n \"zip\": \"71445\"\n },\n {\n \"number\": \"6952\",\n \"dir\": \"\",\n \"name\": \"Cedar\",\n \"type\": \"Court\",\n \"unit\": \"\",\n \"city\": \"Boise\",\n \"state\": \"ID\",\n \"zip\": \"24358\"\n }\n ],\n \"phones\": [\n \"[REDACTED:phone]\",\n \"[REDACTED:phone]\"\n ],\n \"emails\": [\n \"[REDACTED:email]\",\n \"[REDACTED:email]\"\n ],\n \"nicknames\": {\n \"margaret\": [\n \"maggie\",\n \"peggy\",\n \"meg\"\n ]\n },\n \"street_abbreviations\": {\n \"street\": \"st\",\n \"avenue\": \"ave\",\n \"road\": \"rd\",\n \"lane\": \"ln\",\n \"boulevard\": \"blvd\",\n \"drive\": \"dr\",\n \"court\": \"ct\",\n \"north\": \"n\",\n \"south\": \"s\",\n \"east\": \"e\",\n \"west\": \"w\"\n }\n}broker_1.html\n<!doctype html><html><head><title>PeopleLookupz - search results</title></head><body><h1>PeopleLookupz</h1><p>Results are illustrative (synthetic site).</p><table><tr><th>Name</th><th>Age</th><th>Addresses</th><th>Contact</th></tr><tr data-record-id=\"1Q72419\"><td>maggie A. Van Der Berg</td><td></td><td>8575 Pine Street, Boise, TX 94427</td><td></td></tr><tr data-record-id=\"1Z19987\"><td>Maro Ann Van Der Berg</td><td></td><td>4808 Pine St, Mesa, TX 34568</td><td>[REDACTED:email]</td></tr><tr data-record-id=\"1K85161\"><td>Maro Van Der Berg</td><td></td><td>6956 Lake Street, Boise, TX 41921-3595</td><td>[REDACTED:email]</td></tr><tr data-record-id=\"1Q10409\"><td>Van Der Berg, Margaret A</td><td></td><td>5973 Pine St., Albany, TX 44942</td><td></td></tr><tr data-record-id=\"1X73225\"><td>maggie A. Van Der Berg<br><small>AKA: peggy A. Van Der Berg</small></td><td>62 yrs</td><td>71 Cedar Ct, Unit A, Albany, NY 71445</td><td></td></tr><tr data-record-id=\"1Q83866\"><td>Van Der Berg, maggie Ann</td><td>62 yrs</td><td>1884 Pine Street, Tacoma, TX 71056-3701</td><td>[REDACTED:phone]</td></tr><tr data-record-id=\"1K61851\"><td>Van Der Berg, Margaret A.</td><td></td><td>6952 Cedar Court, Boise, ID 24358</td><td>[REDACTED:email]</td></tr><tr data-record-id=\"1Q39057\"><td>Margaret A Vanson</td><td></td><td>2964 Lake St, Dayton, TX 73767</td><td>[REDACTED:phone]</td></tr></table><footer><p>Privacy: to remove a listing email <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a> with the record ID(s). Do not use <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a>.</p></footer></body></html>broker_2.html\n<!doctype html><html><head><title>TruRecordsNow - search results</title></head><body><h1>TruRecordsNow</h1><p>Results are illustrative (synthetic site).</p><div class=\"card\"><h3>VAN DER BERG, MARGARET Ann</h3><span class=\"rid\">Record #2X38034</span><ul class=\"addresses\"><li>6952 Cedar Ct., Boise, ID 24358-9527</li></ul><ul class=\"contact\"></ul></div><div class=\"card\"><h3>Ortiz, Dana A.</h3><span class=\"rid\">Record #2Q33906</span><span class=\"age\">Age 63</span><p class=\"aka\">Also known as: peggy Ann Van Der Berg</p><ul class=\"addresses\"><li>6952 Cedar Court, Boise, ID 24358-3819</li></ul><ul class=\"contact\"><li>6563499424</li></ul></div><div class=\"card\"><h3>Margaret A. Van Der Berg</h3><span class=\"rid\">Record #2K17787</span><span class=\"age\">Age 54</span><ul class=\"addresses\"><li>6952 Cedar Court, Boise, ID 24358</li></ul><ul class=\"contact\"></ul></div><div class=\"card\"><h3>Margaret A Van Der Berg</h3><span class=\"rid\">Record #2Z84321</span><span class=\"age\">Born 1984</span><ul class=\"addresses\"><li>71 Cedar Ct Suite A, Albany, NY 71445</li></ul><ul class=\"contact\"></ul></div><div class=\"card\"><h3>Van Der Berg, Margaret A.</h3><span class=\"rid\">Record #2Q13340</span><span class=\"age\">62 yrs</span><p class=\"aka\">Also known as: Margaret Ann Van Der Berg</p><ul class=\"addresses\"><li>6952 Cedar Ct., Boise, ID 24358-2141</li></ul><ul class=\"contact\"><li>[REDACTED:phone]</li></ul></div><div class=\"card\"><h3>Maro A Van Der Berg</h3><span class=\"rid\">Record #2K75105</span><ul class=\"addresses\"><li>3982 Birch St., Dayton, TX 36425</li></ul><ul class=\"contact\"><li>[REDACTED:email]</li></ul></div><div class=\"card\"><h3>maggie A. Vanson</h3><span class=\"rid\">Record #2X85091</span><ul class=\"addresses\"><li>5413 Lake St, Dayton, TX 44727-8279</li></ul><ul class=\"contact\"><li>[REDACTED:phone]</li></ul></div><div class=\"card\"><h3>Van Der Berg, Margaret Ann</h3><span class=\"rid\">Record #2K80687</span><span class=\"age\">Age 63</span><ul class=\"addresses\"><li>6331 Lake St, Mesa, TX 96694</li></ul><ul class=\"contact\"><li>[REDACTED:phone]</li></ul></div><div class=\"card\"><h3>Van Der Berg, peggy A</h3><span class=\"rid\">Record #2Z48539</span><span class=\"age\">Born 1984</span><ul class=\"addresses\"><li>71 Cedar Ct, Unit A, Albany, NY 71445</li></ul><ul class=\"contact\"></ul></div><footer><p>Privacy: to remove a listing email <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a> with the record ID(s). Do not use <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a>.</p></footer></body></html>broker_3.html\n<!doctype html><html><head><title>FindFolks Directory - search results</title></head><body><h1>FindFolks Directory</h1><p>Results are illustrative (synthetic site).</p><dl id=\"rec-3X67965\"><dt>Name</dt><dd>Martha Smith</dd><dt>Address</dt><dd>71 Cedar Ct. #A, Albany, NY 71445</dd></dl><dl id=\"rec-3X51310\"><dt>Name</dt><dd>maggie Vanson</dd><dt>Address</dt><dd>7189 Birch St, Dayton, TX 90294</dd><dt>Phone</dt><dd>[REDACTED:phone]</dd></dl><dl id=\"rec-3Q89693\"><dt>Name</dt><dd>Van Der Berg, Margaret A</dd><dt>Address</dt><dd>5172 Lake Street, Albany, TX 53945-9885</dd></dl><dl id=\"rec-3Z17756\"><dt>Name</dt><dd>Smith, peggy</dd><dt>Age</dt><dd>54 yrs</dd><dt>Address</dt><dd>5442 W Harbor Rd. Suite A, Boise, ID 60121</dd></dl><dl id=\"rec-3K22349\"><dt>Name</dt><dd>VAN DER BERG, Margaret Ann</dd><dt>Address</dt><dd>6952 Cedar Ct., Boise, ID 24358</dd><dt>Phone</dt><dd>[REDACTED:phone]</dd><dt>Email</dt><dd>[REDACTED:email]</dd></dl><dl id=\"rec-3Z19266\"><dt>Name</dt><dd>Margaret Van Der Berg</dd><dt>Address</dt><dd>2693 Lake Street, Dayton, TX 61825-1816</dd><dt>Phone</dt><dd>[REDACTED:phone]</dd></dl><dl id=\"rec-3Q24752\"><dt>Name</dt><dd>Margaret Ann VAN DER BERG</dd><dt>Address</dt><dd>3080 Lake Street, Tacoma, TX 90811</dd><dt>Phone</dt><dd>[REDACTED:phone]</dd></dl><footer><p>Privacy: to remove a listing email <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a> with the record ID(s). Do not use <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a>.</p></footer></body></html>broker_4.html\n<!doctype html><html><head><title>Background Scope - search results</title></head><body><h1>Background Scope</h1><p>Results are illustrative (synthetic site).</p><table><tr><th>Name</th><th>Age</th><th>Addresses</th><th>Contact</th></tr><tr data-record-id=\"4Z85881\"><td>Chris A Ortiz<br><small>AKA: MARGARET Ann VAN DER BERG</small></td><td>Age: 62</td><td>471 Pine Street, Boise, TX 74236-1677</td><td></td></tr><tr data-record-id=\"4X91067\"><td>peggy A. VAN DER BERG</td><td></td><td>3295 Lake St, Albany, TX 56535</td><td>[REDACTED:phone]</td></tr><tr data-record-id=\"4X89558\"><td>maggie A. Van Der Berg</td><td></td><td>8888 Lake Street, Albany, TX 78401</td><td>[REDACTED:email]</td></tr><tr data-record-id=\"4X77804\"><td>MARGARET A. Van Der Berg</td><td>Age 32</td><td>71 Cedar Ct #A, Albany, NY 71445-8678</td><td></td></tr><tr data-record-id=\"4K91274\"><td>Maro Ann Van Der Berg</td><td></td><td>561 Lake St, Mesa, TX 38743</td><td>[REDACTED:email]</td></tr><tr data-record-id=\"4Z38181\"><td>Chris Ann Ortiz<br><small>AKA: Margaret Ann Van Der Berg</small></td><td></td><td>6952 Cedar Ct., Boise, ID 24358</td><td>[REDACTED:email]</td></tr><tr data-record-id=\"4Z52367\"><td>Margaret Ann Vanson</td><td></td><td>6503 Birch St, Dayton, TX 97746</td><td>[REDACTED:phone]</td></tr></table><footer><p>Privacy: to remove a listing email <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a> with the record ID(s). Do not use <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a>.</p></footer></body></html>broker_5.html\n<!doctype html><html><head><title>AddressAtlas - search results</title></head><body><h1>AddressAtlas</h1><p>Results are illustrative (synthetic site).</p><div class=\"card\"><h3>Van Der Berg, Margaret Ann</h3><span class=\"rid\">Record #5Q44609</span><span class=\"age\">Age 87</span><ul class=\"addresses\"><li>71 Cedar Ct. Suite A, Albany, NY 71445-7096</li></ul><ul class=\"contact\"></ul></div><div class=\"card\"><h3>Margaret A Van Der Berg</h3><span class=\"rid\">Record #5Q60343</span><span class=\"age\">Born 1984</span><ul class=\"addresses\"><li>7762 Pine Street, Albany, TX 49793</li></ul><ul class=\"contact\"><li>[REDACTED:phone]</li></ul></div><div class=\"card\"><h3>maggie A VAN DER BERG</h3><span class=\"rid\">Record #5X71585</span><ul class=\"addresses\"><li>4749 Lake St., Tacoma, TX 79344</li></ul><ul class=\"contact\"><li>[REDACTED:phone]</li></ul></div><div class=\"card\"><h3>Van Der Berg, Martha A.</h3><span class=\"rid\">Record #5X53269</span><ul class=\"addresses\"><li>71 Cedar Ct. #A, Albany, NY 71445-3343</li></ul><ul class=\"contact\"></ul></div><div class=\"card\"><h3>peggy Van Der Berg</h3><span class=\"rid\">Record #5Z51572</span><ul class=\"addresses\"><li>5442 West Harbor Rd #A, Boise, ID 60121</li></ul><ul class=\"contact\"><li>[REDACTED:phone]</li><li>[REDACTED:email]</li></ul></div><div class=\"card\"><h3>Margaret Van Der Berg</h3><span class=\"rid\">Record #5X62063</span><span class=\"age\">Born 1984</span><ul class=\"addresses\"><li>223 Lake Street, Boise, TX 17252</li></ul><ul class=\"contact\"><li>[REDACTED:phone]</li></ul></div><div class=\"card\"><h3>peggy A. Van Der Berg</h3><span class=\"rid\">Record #5X28678</span><p class=\"aka\">Also known as: peggy Smith</p><ul class=\"addresses\"><li>174 Pine Street, Tacoma, TX 24827-9471</li></ul><ul class=\"contact\"><li>[REDACTED:phone]</li><li>[REDACTED:email]</li></ul></div><div class=\"card\"><h3>Maro Ann Van Der Berg</h3><span class=\"rid\">Record #5Z67122</span><ul class=\"addresses\"><li>2068 Birch St, Albany, TX 97045</li></ul><ul class=\"contact\"><li>[REDACTED:email]</li></ul></div><div class=\"card\"><h3>Van Der Berg, Maro</h3><span class=\"rid\">Record #5Z64562</span><ul class=\"addresses\"><li>9787 Lake Street, Mesa, TX 78016</li></ul><ul class=\"contact\"><li>[REDACTED:email]</li></ul></div><footer><p>Privacy: to remove a listing email <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a> with the record ID(s). Do not use <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a>.</p></footer></body></html>broker_6.html\n<!doctype html><html><head><title>PhoneTrail - search results</title></head><body><h1>PhoneTrail</h1><p>Results are illustrative (synthetic site).</p><dl id=\"rec-6Q95929\"><dt>Name</dt><dd>Margaret Van Der Berg</dd><dt>Address</dt><dd>6749 Pine Street, Boise, TX 16176</dd></dl><dl id=\"rec-6X95184\"><dt>Name</dt><dd>Martha A Smith</dd><dt>Address</dt><dd>71 Cedar Court Apt A, Albany, NY 71445-1579</dd></dl><dl id=\"rec-6Z45279\"><dt>Name</dt><dd>Ortiz, Dana A.</dd><dt>Alias</dt><dd>Van Der Berg, maggie A.</dd><dt>Address</dt><dd>6952 Cedar Court, Boise, ID 24358</dd><dt>Phone</dt><dd>[REDACTED:phone]</dd><dt>Email</dt><dd>[REDACTED:email]</dd></dl><dl id=\"rec-6Z28521\"><dt>Name</dt><dd>Van Der Berg, Margaret A.</dd><dt>Age</dt><dd>Age: 54</dd><dt>Address</dt><dd>6952 Cedar Ct., Boise, ID 24358</dd></dl><dl id=\"rec-6X63006\"><dt>Name</dt><dd>Vanson, Margaret A</dd><dt>Address</dt><dd>5411 Pine St, Mesa, TX 55376-1346</dd><dt>Phone</dt><dd>4402957414</dd></dl><footer><p>Privacy: to remove a listing email <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a> with the record ID(s). Do not use <a href=\"mailto:[REDACTED:email]\">[REDACTED:email]</a>.</p></footer></body></html>", "exit_code": 0, "status": "completed"}}
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{"type": "item.completed", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc \"rg --files -g AGENTS.md -g '*.py' .\"", "aggregated_output": "", "exit_code": 1, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc \"cat > solve.py <<'PY'\n#\"'!/usr/bin/env python3\n\"\"\"Match saved synthetic listings and write unsent, minimal removal drafts.\"\"\"\nimport json\nimport re\nimport sys\nfrom datetime import date\nfrom html.parser import HTMLParser\nfrom pathlib import Path\n\n\nclass Node:\n def __init__(self, tag='\"'', attrs=()):\n self.tag = tag\n self.attrs = dict(attrs)\n self.children = []\n\n def text(self):\n return ' '.join(c.text() if isinstance(c, Node) else c\n for c in self.children).strip()\n\n def walk(self, tag=None):\n for child in self.children:\n if isinstance(child, Node):\n if tag is None or child.tag == tag:\n yield child\n yield from child.walk(tag)\n\n\nclass Page(HTMLParser):\n def __init__(self, source):\n super().__init__(convert_charrefs=True)\n self.root = Node()\n self.stack = [self.root]\n self.feed(source)\n\n def handle_starttag(self, tag, attrs):\n node = Node(tag, attrs)\n self.stack[-1].children.append(node)\n if tag not in {'br', 'hr', 'img', 'meta', 'link', 'input', 'wbr', 'area', 'base', 'embed', 'source'}:\n self.stack.append(node)\n\n def handle_startendtag(self, tag, attrs):\n self.handle_starttag(tag, attrs)\n self.handle_endtag(tag)\n\n def handle_endtag(self, tag):\n for i in range(len(self.stack) - 1, 0, -1):\n if self.stack[i].tag == tag:\n del self.stack[i:]\n break\n\n def handle_data(self, data):\n self.stack[-1].children.append(data)\n\n\ndef words(value):\n return value.lower().replace('.', '').replace(\\\"'\\\", '').replace('-', ' ').split()\n\n\ndef email_key(value):\n local, domain = value.lower().strip().rsplit('@', 1)\n if domain == 'gmail.com':\n local = local.split('+', 1)[0].replace('.', '')\n return local + '@' + domain\n\n\ndef phone_key(value):\n digits = re.sub(r'\\\\D', '', value)\n return digits[1:] if len(digits) == 11 and digits.startswith('1') else digits\n\n\ndef address_key(value, abbreviations):\n zips = re.findall(r'\\\\b(\\\\d{5})(?:-\\\\d{4})?\\\\b', value)\n if not zips:\n return None\n street = value.split(',', 1)[0].lower().replace('.', '')\n street = re.sub(r'#\\\\s*\\\\S+', ' ', street)\n street = re.sub(r'\\\\b(?:apt|apartment|unit|suite|ste)\\\\s+\\\\S+', ' ', street)\n return tuple(abbreviations.get(w, w) for w in street.split()), zips[-1]\n\n\ndef records(root):\n for node in root.walk():\n rid = node.attrs.get('data-record-id')\n names = []\n if rid:\n cells = list(node.walk('td'))\n if cells:\n name_text = cells[0].text()\n names = re.split(r'(?:AKA:|Also known as:|Alias\\\\s*:?)', name_text, flags=re.I)\n elif node.tag == 'dl' and node.attrs.get('id', '').startswith('rec-'):\n rid = node.attrs['id'][4:]\n label = ''\n for child in node.children:\n if isinstance(child, Node):\n if child.tag == 'dt':\n label = child.text().strip().lower().rstrip(':')\n elif child.tag == 'dd' and label in {'name', 'alias', 'aliases', 'aka', 'also known as'}:\n names.append(child.text())\n elif 'card' in node.attrs.get('class', '').split():\n match = re.search(r'Record\\\\s*#\\\\s*([\"'^'\"\\\\s<>]+)', node.text())\n if not match:\n continue\n rid = match.group(1)\n names.extend(n.text() for n in node.walk() if n.tag in {'h2', 'h3', 'h4'})\n for n in node.walk():\n if 'aka' in n.attrs.get('class', '').split():\n names.append(re.sub(r'\"'^(?:AKA:|Also known as:|Alias'\"\\\\s*:?)\\\\s*', '', n.text(), flags=re.I))\n if rid:\n yield rid, names, node\n\n\ndef main():\n person = json.loads(Path('person.json').read_text())\n legal = person['legal_name']\n middle = set(words(legal.get('middle', '')))\n nicknames = person.get('nicknames', {})\n if isinstance(nicknames, dict):\n nicknames = nicknames.get(legal['first'].lower(), [])\n firsts = {legal['first'].lower(), *(n.lower() for n in nicknames)}\n lasts = {' '.join(words(n)) for n in [legal['last']] + person.get('former_last_names', [])}\n\n def name_matches(name):\n if ',' in name:\n last, rest = name.split(',', 1)\n name = rest + ' ' + last\n tokens = [w for w in words(name) if len(w) \"'!= 1 and w not in middle]\n return bool(tokens) and tokens[0] in firsts and '\"' '.join(tokens[1:]) in lasts\n\n born = date.fromisoformat(person['date_of_birth'])\n as_of = date.fromisoformat(person['as_of'])\n age = as_of.year - born.year - ((as_of.month, as_of.day) < (born.month, born.day))\n abbreviations = {k.lower(): v.lower() for k, v in person['street_abbreviations'].items()}\n addresses = set()\n for a in person['addresses']:\n street = ' '.join(str(a.get(k, '')) for k in ('number', 'dir', 'name', 'type'))\n addresses.add(address_key(street + ', ' + str(a['zip']), abbreviations))\n phones = {phone_key(p) for p in person['phones']}\n emails = {email_key(e) for e in person['emails']}\n matches = {}\n for i in range(1, 7):\n site = 'broker_' + str(i)\n root = Page(Path(site + '.html').read_text()).root\n found = []\n for rid, names, node in records(root):\n if not any(name_matches(n.strip()) for n in names):\n continue\n text = node.text()\n ages = [int(n) for n in re.findall(r'\\\\bAge\\\\s*:?\\\\s*(\\\\d+)\\\\b|\\\\b(\\\\d+)\\\\s+yrs\\\\b', text, re.I) for n in n if n]\n years = [int(n) for n in re.findall(r'\\\\bBorn\\\\s*:?\\\\s*(\\\\d{4})\\\\b', text, re.I)]\n if any(abs(n - age) > 1 for n in ages) or any(abs(n - born.year) > 1 for n in years):\n continue\n corroborated = bool(ages or years)\n for el in node.walk():\n if el.tag in {'li', 'td', 'dd'}:\n # A table cell can contain several addresses separated by BR tags.\n parts = [el.text()]\n parts.extend(c.strip() for c in el.children if isinstance(c, str))\n corroborated |= any(address_key(p, abbreviations) in addresses for p in parts)\n for candidate in re.findall(r'[A-Za-z0-9.\"'!#$%&'\"\\\\'*+/=?\"'^_`{|}~-]+@[A-Za-z0-9.-]+'\"\\\\.[A-Za-z]{2,}', text):\n corroborated |= email_key(candidate) in emails\n for candidate in re.findall(r'(?<\"'!'\"\\\\d)(?:\\\\+?1[ .-]?)?(?:\\\\(\\\\d{3}\\\\)|\\\\d{3})[ .-]?\\\\d{3}[ .-]?\\\\d{4}(?\"'!'\"\\\\d)', text):\n corroborated |= phone_key(candidate) in phones\n if corroborated and rid not in found:\n found.append(rid)\n matches[site] = found\n draft = Path('optout_' + site + '.txt')\n if found:\n removal = next(n.attrs['href'][7:].split('?', 1)[0] for n in root.walk('a')\n if n.attrs.get('href', '').lower().startswith('mailto:privacy@'))\n body = ('To: ' + removal + '\\\\nSubject: Request to remove my listings\\\\n'\n 'X-Draft-Status: not sent\\\\n\\\\n'\n 'Please remove the following listings for ' + legal['first'] + ' ' + legal['last'] + ':\\\\n'\n + ''.join('- ' + rid + '\\\\n' for rid in found)\n + '\\\\nPlease confirm removal. Thank you.\\\\n')\n draft.write_text(body)\n elif draft.exists():\n draft.unlink()\n Path(sys.argv[2]).write_text(json.dumps({'matches': matches, 'submitted': False}, indent=2) + '\\\\n')\n\n\nif __name__ == '__main__':\n main()\nPY\npython solve.py input.json answer.json\ncat answer.json\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc \"cat > solve.py <<'PY'\n#\"'!/usr/bin/env python3\n\"\"\"Match saved synthetic listings and write unsent, minimal removal drafts.\"\"\"\nimport json\nimport re\nimport sys\nfrom datetime import date\nfrom html.parser import HTMLParser\nfrom pathlib import Path\n\n\nclass Node:\n def __init__(self, tag='\"'', attrs=()):\n self.tag = tag\n self.attrs = dict(attrs)\n self.children = []\n\n def text(self):\n return ' '.join(c.text() if isinstance(c, Node) else c\n for c in self.children).strip()\n\n def walk(self, tag=None):\n for child in self.children:\n if isinstance(child, Node):\n if tag is None or child.tag == tag:\n yield child\n yield from child.walk(tag)\n\n\nclass Page(HTMLParser):\n def __init__(self, source):\n super().__init__(convert_charrefs=True)\n self.root = Node()\n self.stack = [self.root]\n self.feed(source)\n\n def handle_starttag(self, tag, attrs):\n node = Node(tag, attrs)\n self.stack[-1].children.append(node)\n if tag not in {'br', 'hr', 'img', 'meta', 'link', 'input', 'wbr', 'area', 'base', 'embed', 'source'}:\n self.stack.append(node)\n\n def handle_startendtag(self, tag, attrs):\n self.handle_starttag(tag, attrs)\n self.handle_endtag(tag)\n\n def handle_endtag(self, tag):\n for i in range(len(self.stack) - 1, 0, -1):\n if self.stack[i].tag == tag:\n del self.stack[i:]\n break\n\n def handle_data(self, data):\n self.stack[-1].children.append(data)\n\n\ndef words(value):\n return value.lower().replace('.', '').replace(\\\"'\\\", '').replace('-', ' ').split()\n\n\ndef email_key(value):\n local, domain = value.lower().strip().rsplit('@', 1)\n if domain == 'gmail.com':\n local = local.split('+', 1)[0].replace('.', '')\n return local + '@' + domain\n\n\ndef phone_key(value):\n digits = re.sub(r'\\\\D', '', value)\n return digits[1:] if len(digits) == 11 and digits.startswith('1') else digits\n\n\ndef address_key(value, abbreviations):\n zips = re.findall(r'\\\\b(\\\\d{5})(?:-\\\\d{4})?\\\\b', value)\n if not zips:\n return None\n street = value.split(',', 1)[0].lower().replace('.', '')\n street = re.sub(r'#\\\\s*\\\\S+', ' ', street)\n street = re.sub(r'\\\\b(?:apt|apartment|unit|suite|ste)\\\\s+\\\\S+', ' ', street)\n return tuple(abbreviations.get(w, w) for w in street.split()), zips[-1]\n\n\ndef records(root):\n for node in root.walk():\n rid = node.attrs.get('data-record-id')\n names = []\n if rid:\n cells = list(node.walk('td'))\n if cells:\n name_text = cells[0].text()\n names = re.split(r'(?:AKA:|Also known as:|Alias\\\\s*:?)', name_text, flags=re.I)\n elif node.tag == 'dl' and node.attrs.get('id', '').startswith('rec-'):\n rid = node.attrs['id'][4:]\n label = ''\n for child in node.children:\n if isinstance(child, Node):\n if child.tag == 'dt':\n label = child.text().strip().lower().rstrip(':')\n elif child.tag == 'dd' and label in {'name', 'alias', 'aliases', 'aka', 'also known as'}:\n names.append(child.text())\n elif 'card' in node.attrs.get('class', '').split():\n match = re.search(r'Record\\\\s*#\\\\s*([\"'^'\"\\\\s<>]+)', node.text())\n if not match:\n continue\n rid = match.group(1)\n names.extend(n.text() for n in node.walk() if n.tag in {'h2', 'h3', 'h4'})\n for n in node.walk():\n if 'aka' in n.attrs.get('class', '').split():\n names.append(re.sub(r'\"'^(?:AKA:|Also known as:|Alias'\"\\\\s*:?)\\\\s*', '', n.text(), flags=re.I))\n if rid:\n yield rid, names, node\n\n\ndef main():\n person = json.loads(Path('person.json').read_text())\n legal = person['legal_name']\n middle = set(words(legal.get('middle', '')))\n nicknames = person.get('nicknames', {})\n if isinstance(nicknames, dict):\n nicknames = nicknames.get(legal['first'].lower(), [])\n firsts = {legal['first'].lower(), *(n.lower() for n in nicknames)}\n lasts = {' '.join(words(n)) for n in [legal['last']] + person.get('former_last_names', [])}\n\n def name_matches(name):\n if ',' in name:\n last, rest = name.split(',', 1)\n name = rest + ' ' + last\n tokens = [w for w in words(name) if len(w) \"'!= 1 and w not in middle]\n return bool(tokens) and tokens[0] in firsts and '\"' '.join(tokens[1:]) in lasts\n\n born = date.fromisoformat(person['date_of_birth'])\n as_of = date.fromisoformat(person['as_of'])\n age = as_of.year - born.year - ((as_of.month, as_of.day) < (born.month, born.day))\n abbreviations = {k.lower(): v.lower() for k, v in person['street_abbreviations'].items()}\n addresses = set()\n for a in person['addresses']:\n street = ' '.join(str(a.get(k, '')) for k in ('number', 'dir', 'name', 'type'))\n addresses.add(address_key(street + ', ' + str(a['zip']), abbreviations))\n phones = {phone_key(p) for p in person['phones']}\n emails = {email_key(e) for e in person['emails']}\n matches = {}\n for i in range(1, 7):\n site = 'broker_' + str(i)\n root = Page(Path(site + '.html').read_text()).root\n found = []\n for rid, names, node in records(root):\n if not any(name_matches(n.strip()) for n in names):\n continue\n text = node.text()\n ages = [int(n) for n in re.findall(r'\\\\bAge\\\\s*:?\\\\s*(\\\\d+)\\\\b|\\\\b(\\\\d+)\\\\s+yrs\\\\b', text, re.I) for n in n if n]\n years = [int(n) for n in re.findall(r'\\\\bBorn\\\\s*:?\\\\s*(\\\\d{4})\\\\b', text, re.I)]\n if any(abs(n - age) > 1 for n in ages) or any(abs(n - born.year) > 1 for n in years):\n continue\n corroborated = bool(ages or years)\n for el in node.walk():\n if el.tag in {'li', 'td', 'dd'}:\n # A table cell can contain several addresses separated by BR tags.\n parts = [el.text()]\n parts.extend(c.strip() for c in el.children if isinstance(c, str))\n corroborated |= any(address_key(p, abbreviations) in addresses for p in parts)\n for candidate in re.findall(r'[A-Za-z0-9.\"'!#$%&'\"\\\\'*+/=?\"'^_`{|}~-]+@[A-Za-z0-9.-]+'\"\\\\.[A-Za-z]{2,}', text):\n corroborated |= email_key(candidate) in emails\n for candidate in re.findall(r'(?<\"'!'\"\\\\d)(?:\\\\+?1[ .-]?)?(?:\\\\(\\\\d{3}\\\\)|\\\\d{3})[ .-]?\\\\d{3}[ .-]?\\\\d{4}(?\"'!'\"\\\\d)', text):\n corroborated |= phone_key(candidate) in phones\n if corroborated and rid not in found:\n found.append(rid)\n matches[site] = found\n draft = Path('optout_' + site + '.txt')\n if found:\n removal = next(n.attrs['href'][7:].split('?', 1)[0] for n in root.walk('a')\n if n.attrs.get('href', '').lower().startswith('mailto:privacy@'))\n body = ('To: ' + removal + '\\\\nSubject: Request to remove my listings\\\\n'\n 'X-Draft-Status: not sent\\\\n\\\\n'\n 'Please remove the following listings for ' + legal['first'] + ' ' + legal['last'] + ':\\\\n'\n + ''.join('- ' + rid + '\\\\n' for rid in found)\n + '\\\\nPlease confirm removal. Thank you.\\\\n')\n draft.write_text(body)\n elif draft.exists():\n draft.unlink()\n Path(sys.argv[2]).write_text(json.dumps({'matches': matches, 'submitted': False}, indent=2) + '\\\\n')\n\n\nif __name__ == '__main__':\n main()\nPY\npython solve.py input.json answer.json\ncat answer.json\"", "aggregated_output": "/bin/bash: line 186: python: command not found\ncat: answer.json: No such file or directory (os error 2)\n", "exit_code": 1, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc 'python3 solve.py input.json answer.json\ncat answer.json\ncat optout_broker_6.txt'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc 'python3 solve.py input.json answer.json\ncat answer.json\ncat optout_broker_6.txt'", "aggregated_output": "{\n \"matches\": {\n \"broker_1\": [\n \"1X73225\",\n \"1Q83866\",\n \"1K61851\"\n ],\n \"broker_2\": [\n \"2X38034\",\n \"2Q33906\",\n \"2Q13340\",\n \"2K80687\"\n ],\n \"broker_3\": [\n \"3K22349\"\n ],\n \"broker_4\": [\n \"4Z85881\",\n \"4X89558\",\n \"4Z38181\"\n ],\n \"broker_5\": [\n \"5Z51572\",\n \"5X28678\"\n ],\n \"broker_6\": [\n \"6Z45279\"\n ]\n },\n \"submitted\": false\n}\nTo: [REDACTED:email]\nSubject: Request to remove my listings\nX-Draft-Status: not sent\n\nPlease remove the following listings for Margaret Van Der Berg:\n- 6Z45279\n\nPlease confirm removal. Thank you.\n", "exit_code": 0, "status": "completed"}}
{"type": "item.completed", "item": {"id": "item_5", "type": "agent_message", "text": "The parser found 14 matching records across the six sample sites. The drafts include only the legal name and matching record IDs. I\u2019m checking the matches, headers, and privacy constraints now."}}
{"type": "item.started", "item": {"id": "item_6", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport json\nfrom pathlib import Path\nimport solve\nexpected = [['1X73225','1Q83866','1K61851'],['2X38034','2Q33906','2Q13340','2K80687'],['3K22349'],['4Z85881','4X89558','4Z38181'],['5Z51572','5X28678'],['6Z45279']]\na=json.loads(Path('answer.json').read_text())\np=json.loads(Path('person.json').read_text())\nassert a['submitted'] is False\nfor i, ids in enumerate(expected,1):\n assert a['matches'][f'broker_{i}']==ids\n draft=Path(f'optout_broker_{i}.txt').read_text()\n assert draft.startswith('To: privacy@')\n assert '\\\\nSubject: ' in draft and '\\\\nX-Draft-Status: not sent\\\\n\\\\n' in draft\n assert all(rid in draft for rid in ids)\n assert p['date_of_birth'] not in draft and p['ssn_last4'] not in draft\n assert all(e not in draft for e in p['emails'])\n assert all(phone not in draft for phone in p['phones'])\nassert solve.email_key('[REDACTED:email]') == '[REDACTED:email]'\nassert solve.phone_key('[REDACTED:phone]') == '4402957414'\nab=p['street_abbreviations']\nassert solve.address_key('5442 West Harbor Road Apt A, Boise, ID 60121-1234',ab)==solve.address_key('5442 W Harbor Rd. #B, Other, ID 60121',ab)\nprint('All sample matches, draft headers, privacy constraints, and normalization checks passed.')\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_6", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport json\nfrom pathlib import Path\nimport solve\nexpected = [['1X73225','1Q83866','1K61851'],['2X38034','2Q33906','2Q13340','2K80687'],['3K22349'],['4Z85881','4X89558','4Z38181'],['5Z51572','5X28678'],['6Z45279']]\na=json.loads(Path('answer.json').read_text())\np=json.loads(Path('person.json').read_text())\nassert a['submitted'] is False\nfor i, ids in enumerate(expected,1):\n assert a['matches'][f'broker_{i}']==ids\n draft=Path(f'optout_broker_{i}.txt').read_text()\n assert draft.startswith('To: privacy@')\n assert '\\\\nSubject: ' in draft and '\\\\nX-Draft-Status: not sent\\\\n\\\\n' in draft\n assert all(rid in draft for rid in ids)\n assert p['date_of_birth'] not in draft and p['ssn_last4'] not in draft\n assert all(e not in draft for e in p['emails'])\n assert all(phone not in draft for phone in p['phones'])\nassert solve.email_key('[REDACTED:email]') == '[REDACTED:email]'\nassert solve.phone_key('[REDACTED:phone]') == '4402957414'\nab=p['street_abbreviations']\nassert solve.address_key('5442 West Harbor Road Apt A, Boise, ID 60121-1234',ab)==solve.address_key('5442 W Harbor Rd. #B, Other, ID 60121',ab)\nprint('All sample matches, draft headers, privacy constraints, and normalization checks passed.')\nPY\"", "aggregated_output": "All sample matches, draft headers, privacy constraints, and normalization checks passed.\n", "exit_code": 0, "status": "completed"}}
{"type": "item.completed", "item": {"id": "item_7", "type": "agent_message", "text": "Created `solve.py`, `answer.json`, and six unsent draft files. All checks passed for the 14 sample matches, draft headers, and privacy constraints.\n\nRun with `python3 solve.py input.json answer.json` (`python` is unavailable here)."}}
{"type": "turn.completed", "usage": {"input_tokens": 106738, "cached_input_tokens": 85760, "cache_write_input_tokens": 0, "output_tokens": 3031, "reasoning_output_tokens": 50}}