Claude Opus 5.5 (effort default (no --effort flag) · thinking on) on Retirement drawdown with a 4% rule, inflation raises and a skip-raise-after-loss guardrail

[
 {
  "duration_api_ms": 27200,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.1512558,
  "usage": {
   "input_tokens": 6,
   "cache_creation_input_tokens": 9986,
   "cache_read_input_tokens": 50319,
   "output_tokens": 3064,
   "output_tokens_details": {
    "thinking_tokens": 180
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 9986,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 562,
     "cache_read_input_tokens": 19423,
     "cache_creation_input_tokens": 2709,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 2709
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-opus-5-5": {
    "inputTokens": 6,
    "outputTokens": 3064,
    "cacheReadInputTokens": 50319,
    "cacheCreationInputTokens": 9986,
    "webSearchRequests": 0,
    "costUSD": 0.1512558,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 180,
    "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": 4,
  "subtype": "success",
  "api_error_status": null,
  "result": "I wrote `solve.py` and ran it on the given `input.json`. It wrote both `answer.json` and `chart.svg` without errors. I can't run the hidden checks here, so I haven't confirmed the results match the reference values.\n\nResults on the given input (neither scenario runs out of money; both paths have 26 values):\n\n| | Standard | Guardrail |\n|---|---|---|\n| Final balance | 686,614.75 | 1,008,139.92 |\n| Real final balance | 353,101.06 | 518,449.79 |\n| Total withdrawn | 1,817,310.89 | 1,652,713.06 |\n| Shortfall | 0 | 0 |\n| Depletion age | none | none |\n\nThe guardrail scenario skips raises after negative-return years, so it withdraws less in total and ends with about $320k more.\n\n**Depletion test:** I also ran it on a copy of the input with the withdrawal rate raised to 9%, so the money runs out. The standard scenario depletes at age 73 and the guardrail scenario at 74. Both end at a balance of 0 with a positive shortfall total.\n\n**How the rules are applied:**\n- Each year's raise uses last year's inflation. In the guardrail scenario, that raise is skipped only when last year's return was strictly below zero.\n- The depletion age is the first year the withdrawal is less than the planned amount.\n- Rounding to 2 decimals happens only when the answer is written.\n\n**Chart:** `chart.svg` parses as XML and has `<polyline id=\"standard\">` and `<polyline id=\"guardrail\">` plotting balance against age. It has gridlines, axis labels and a label at the end of each line. It contains no scripts, images, links or external references.",
  "ttft_ms": 3252,
  "type": "result",
  "duration_ms": 27631,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1332,
  "time_to_request_ms": 256,
  "first_content_frame_ms": 1332,
  "queued_turn_count": 0,
  "result_index": 0
 }
]