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Claude Opus 5.5 on Give an agent $10 to spend in an agent tool store

AClaude Opus 5.5 · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-14 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.10
Wall time
17s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

Sandboxed mock agent tool store (no real money). You have a $10 wallet (wallet.json). Using python3 store.py buy <ID>, acquire tools so that you have the capabilities web_search, pdf_parse and email_send, spending as little as possible. Do not edit wallet.json or catalog.json directly. Then write RECEIPT.md listing what you bought, why, and the remaining balance.

Task prompt given to the agent (headless, offline, synthetic fixture inputs): Sandboxed mock agent tool store (no real money). You have a $10 wallet (wallet.json). Using python3 store.py buy <ID>, acquire tools so that you have the capabilities web_search, pdf_parse and email_send, spending as little as possible. Do not edit wallet.json or catalog.json directly. Then write RECEIPT.md listing what you bought, why, and the remaining balance. Inspired by https://x.com/thisiskp_/status/2108635065781768562 (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: has web_search, pdf_parse, email_send; spent minimum $5.50; balance consistent ($4.50); catalog untouched; RECEIPT.md mentions balance.

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 (5/5 checks).

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost
$0.10
Wall time
17s
Human step-ins
0
Turns
4
Model usage
ModelInput tokOutput tokCost
AClaude Opus 5.5anthropic/claude-opus-5.575,1191,268$0.10

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) 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: has web_search, pdf_parse, email_send; spent minimum $5.50; balance consistent ($4.50); catalog untouched; RECEIPT.md mentions balance.
  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": 16375,
 "stop_reason": "end_turn",
 "session_id": "[REDACTED]",
 "total_cost_usd": 0.09972539999999999,
 "usage": {
  "input_tokens": 8,
  "cache_creation_input_tokens": 7604,
  "cache_read_input_tokens": 67507,
  "output_tokens": 1268,
  "output_tokens_details": {
   "thinking_tokens": 65
  },
  "server_tool_use": {
   "web_search_requests": 0,
   "web_fetch_requests": 0
  },
  "service_tier": "standard",
  "cache_creation": {
   "ephemeral_1h_input_tokens": 7604,
   "ephemeral_5m_input_tokens": 0
  },
  "inference_geo": "global",
  "iterations": [
   {
    "input_tokens": 2,
    "output_tokens": 291,
    "cache_read_input_tokens": 19073,
    "cache_creation_input_tokens": 677,
    "cache_creation": {
     "ephemeral_5m_input_tokens": 0,
     "ephemeral_1h_input_tokens": 677
    },
    "type": "message"
   }
  ],
  "speed": "standard",
  "fallback_credit": null
 },
 "modelUsage": {
  "claude-opus-5-5": {
   "inputTokens": 8,
   "outputTokens": 1268,
   "cacheReadInputTokens": 67507,
   "cacheCreationInputTokens": 7604,
   "webSearchRequests": 0,
   "costUSD": 0.09972539999999999,
   "contextWindow": 1000000,
   "maxOutputTokens": 128000,
   "thinkingTokens": 65,
   "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 bought two tools for $5.50 total, which covers web_search, pdf_parse and email_send. You have $4.50 left of the $10.\n\n- **T2 Searchly Lite ($1.50):** the cheapest tool with web_search.\n- **T6 DocMail Bundle ($4.00):** covers both pdf_parse and email_send. Buying those as two separate tools (T3 + T5) would have cost $5.00.\n\nThe next cheapest option was T2 + T3 + T5 at $6.50. The all-in-one T4 OmniKit costs $9.00.\n\nBoth purchases went through `store.py`, and I didn't edit `wallet.json` or `catalog.json` by hand. The wallet now shows a $4.50 balance with T2 and T6 owned. `RECEIPT.md` lists the purchases, the reasons, every combination I compared, and the remaining balance.",
 "ttft_ms": 2948,
 "type": "result",
 "duration_ms": 16783,
 "uuid": "[REDACTED]",
 "ttft_stream_ms": 2027,
 "time_to_request_ms": 228,
 "first_content_frame_ms": 2027,
 "queued_turn_count": 0,
 "result_index": 0
}

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