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Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Call a car rental company to add an infant seat

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

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.0045
Wall time
17s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

This is a sandboxed simulated phone call (no real call). booking.json describes my car rental and what I need. Each turn of the call is: python3 ivr.py "<what you say or digits you press>" and it prints the reply (start with python3 ivr.py "" to dial). Navigate the menu, reach a person, make exactly the change in booking.json, ask for an emailed confirmation, and end the call politely. Don't make any other changes. Do not read or edit ivr.py or call_state.json; interact only by calling it. Finally write CALL_SUMMARY.md.

Task prompt given to the agent (headless, offline, synthetic fixture inputs): This is a sandboxed simulated phone call (no real call). booking.json describes my car rental and what I need. Each turn of the call is: python3 ivr.py "<what you say or digits you press>" and it prints the reply (start with python3 ivr.py "" to dial). Navigate the menu, reach a person, make exactly the change in booking.json, ask for an emailed confirmation, and end the call politely. Don't make any other changes. Do not read or edit ivr.py or call_state.json; interact only by calling it. Finally write CALL_SUMMARY.md. Inspired by https://agentusecases.ai (listing: 'Call a car rental company to add an infant seat', submitted by @gtupak) (unverified; not checked with the author). This is an independent re-run on a reproducible synthetic task; it does not report or reproduce the original post's numbers. Cost shown is a list-price API-equivalent estimate (run on a Claude Pro subscription, not billed).

Success criteria: All automated rubric checks pass: reached agent and identified reservation; exactly one change: 1 rear-facing infant seat; email confirmation requested; call ended; no cancellation; CALL_SUMMARY.md written.

Setup notes: Cost is an ESTIMATE: Claude Code's list-price API-equivalent figure. The run used a Claude Pro subscription, so nothing was billed. input_tokens = all input incl. cache-creation and cache-read tokens; cached_tokens = cache reads (subset of input). Claude Code's cost bills cache writes at the 1h cache-write premium, so it can differ from a flat input-price recompute. Web disabled; tools Read/Write/Edit/Glob/Grep/Bash; single run; scored automatically (6/6 checks).

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost
$0.0045
Wall time
17s
Human step-ins
0
Turns
11
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on199,2921,773$0.0045

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Claude Haiku 5.5 (anthropic/claude-haiku-5.5, effort default (no --effort flag) · 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 automated rubric checks pass: reached agent and identified reservation; exactly one change: 1 rear-facing infant seat; email confirmation requested; call ended; no cancellation; CALL_SUMMARY.md written.
  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

Trust 80% comes from these checks (how Trust % works).

Evidence log
{
 "duration_api_ms": 15344,
 "stop_reason": "end_turn",
 "session_id": "[REDACTED]",
 "total_cost_usd": 0.004512940000000001,
 "usage": {
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  "cache_read_input_tokens": 190684,
  "output_tokens": 1773,
  "output_tokens_details": {
   "thinking_tokens": 50
  },
  "server_tool_use": {
   "web_search_requests": 0,
   "web_fetch_requests": 0
  },
  "service_tier": "standard",
  "cache_creation": {
   "ephemeral_1h_input_tokens": 8588,
   "ephemeral_5m_input_tokens": 0
  },
  "inference_geo": "global",
  "iterations": [
   {
    "input_tokens": 2,
    "output_tokens": 182,
    "cache_read_input_tokens": 20569,
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    "cache_creation": {
     "ephemeral_5m_input_tokens": 0,
     "ephemeral_1h_input_tokens": 558
    },
    "type": "message"
   }
  ],
  "speed": "standard",
  "fallback_credit": null
 },
 "modelUsage": {
  "claude-haiku-5-5": {
   "inputTokens": 20,
   "outputTokens": 1773,
   "cacheReadInputTokens": 190684,
   "cacheCreationInputTokens": 8588,
   "webSearchRequests": 0,
   "costUSD": 0.004512940000000001,
   "contextWindow": 1000000,
   "maxOutputTokens": 128000,
   "thinkingTokens": 50,
   "canonicalModel": "claude-haiku-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,
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   "system": 0
  },
  "refused": {
   "depth_limit": 0,
   "concurrency_limit": 0,
   "budget": 0
  },
  "by_type": {}
 },
 "safety_stops": 0,
 "is_error": false,
 "num_turns": 11,
 "subtype": "success",
 "api_error_status": null,
 "result": "The call is done. On reservation QX7-48213 (Jordan Lee, BOS, Nov 2 at 10:00), I added one rear-facing infant seat at $13.99/day, and no other changes were made.\n\nThe agent confirmed the seat was added and said the confirmation was emailed to the address on file. I ended the call politely, then wrote the summary to `CALL_SUMMARY.md` in the work directory.\n\nI didn't open `ivr.py` or `call_state.json`; I only read `booking.json` and drove the call through `ivr.py`.",
 "ttft_ms": 1563,
 "type": "result",
 "duration_ms": 16057,
 "uuid": "[REDACTED]",
 "ttft_stream_ms": 1219,
 "time_to_request_ms": 269,
 "first_content_frame_ms": 1219,
 "queued_turn_count": 0,
 "result_index": 0
}

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