Claude Opus 5.5 (effort default (no --effort flag) · thinking on) on Build a leg model from a PDF datasheet that keeps to its real dimensions, servo limits and kinematics

AClaude Opus 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-23 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.14
Wall time: 28s
Human step-ins: 0
Outcome: Pass

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Exact prompt

# Build a leg model from a PDF datasheet that keeps to its real dimensions and limits Inputs: `datasheet.pdf` (a synthetic datasheet for a mock hexapod leg module; `pdftotext -layout datasheet.pdf -` reads it), `poses.json` (servo commands) and `targets.json` (foot targets in the body frame, mm). The datasheet is the record, including any errata it contains. Rules: - Link lengths come from the datasheet in mm (convert inches at 25.4 mm per inch); an erratum replaces the value it corrects. - Joint angles: coxa yaw θ1 = coxa servo − its centre; femur pitch θ2 = femur servo − its horizontal reading, negated if the datasheet says increasing the servo lowers the femur; knee bend k = 180 − tibia servo. Joint limits are the servo stops mapped this way, each written as [low, high]. - Foot position in the leg frame: r = coxa + femur·cos θ2 + tibia·cos(θ2 − k), z = femur·sin θ2 + tibia·sin(θ2 − k), x = r·cos θ1, y = r·sin θ1. The leg frame's origin is the coxa joint, which sits at the datasheet's mount offset in the body frame (body = leg + offset, same axes). - For each target, solve for the unique servo commands with the knee bent (k between 0 and 180) that put the foot there, or mark it "unreachable" if it is out of reach or any servo would pass a stop. - Report servo angles in degrees rounded to 0.01 and positions in mm rounded to 0.01 (servo angles are compared to within 0.02). - Write `out/leg.json`: `{"links_mm": {"coxa": <mm>, "femur": <mm>, "tibia": <mm>}, "joint_limits_deg": {"coxa": [lo, hi], "femur": [lo, hi], "knee": [lo, hi]}, "poses": {"<pose id>": [x, y, z], ...} (foot in the body frame), "ik": {"<target id>": {"coxa": <servo>, "femur": <servo>, "tibia": <servo>} or "unreachable", ...}}`. ## How this run works - Work on your own: nobody will answer questions in this task, and writing to `ask/` counts against the run. - Write only under `out/`. Create `out/` if it is missing. Inputs are synthetic; don't fetch anything from the network. - Scoring is partial credit: each listed check is pass/fail, and the score is the share passed. Numbers are compared to within 0.005 unless the task says otherwise.

Read a synthetic PDF datasheet for a mock hexapod leg and turn it into a working model: link lengths (one in inches, one corrected by an erratum on the second page), joint limits mapped from servo stops with a centre offset, a horizontal reading and a direction note, forward kinematics for given servo poses in the body frame with a mount offset, and inverse kinematics for foot targets including one out of reach and one that would pass a servo stop. 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: links joint_limits forward_kinematics ik_reachable ik_unreachable

Setup notes: Batch 32 case te03-datasheet-leg-model (offline, synthetic inputs, seed 289026244). Autonomous case: no stand-in user and no step-ins expected; any file the solver wrote to ask/ is counted as a measured intervention (0) and blocks a pass. Prompt = TASK.md verbatim. Hidden key kept outside the solver's work dir. Scored with the case's scorer (python3 score.py WORKDIR KEYDIR, absolute paths); pass = every check true and no ask/ files. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. 1-min load average at scoring 0.20 (8 cores). Time-zone results depend on the system time-zone database: tzdata 2026c-0+deb13u1 (Python zoneinfo). Claude Code's own reported cost for claude-opus-5.5: $0.142684. Score: 5/5. 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: $0.14
Wall time: 28s
Human step-ins: 0
Turns: 4

Model usage
Model	Input tok	Output tok	Cost
AClaude Opus 5.5anthropic/claude-opus-5.5effort default (no --effort flag) · thinking on	80,184	2,650	$0.14

Reproduce this run

Use the use case prompt on the use case page.
Same setup: Claude Opus 5.5 (anthropic/claude-opus-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: links joint_limits forward_kinematics ik_reachable ik_unreachable
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": 26470,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.1426836,
  "usage": {
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   "cache_creation_input_tokens": 9438,
   "cache_read_input_tokens": 70738,
   "output_tokens": 2650,
   "output_tokens_details": {
    "thinking_tokens": 625
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 9438,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 754,
     "cache_read_input_tokens": 21120,
     "cache_creation_input_tokens": 464,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 464
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-opus-5-5": {
    "inputTokens": 8,
    "outputTokens": 2650,
    "cacheReadInputTokens": 70738,
    "cacheCreationInputTokens": 9438,
    "webSearchRequests": 0,
    "costUSD": 0.1426836,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 625,
    "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've written `out/leg.json`. Three of the five foot targets have servo solutions, and the other two are marked \"unreachable\". Putting those three solutions back through the forward model lands each foot within about 0.02 mm of its target.\n\n**Lengths and limits from the datasheet**\n- **Links:**\n  - Coxa is 48 mm.\n  - Femur is 3.5433 in \u00d7 25.4 = 89.99982 mm, which rounds to 90.0 mm.\n  - Tibia is 120 mm. That comes from the Rev B erratum, which replaces the 112 mm in the original table.\n- **Mount offset:** (55, \u221218, \u22125) mm.\n- **Joint limits (degrees):**\n  - Coxa is [\u221248, 41]: centre 88, stops 40 to 129.\n  - Femur is [\u221250, 74]. The angle is negated because the datasheet says increasing the femur servo lowers the femur; the horizontal reading is 90 and the stops are 16 to 140.\n  - Knee is [10, 145], from tibia stops 35 to 170.\n\n**Pose foot positions (body frame, mm)**\n\n| Pose | x | y | z |\n|---|---|---|---|\n| P1 | 237.19 | 37.70 | \u2212130.63 |\n| P2 | 92.01 | \u221221.24 | \u221287.73 |\n| P3 | 187.80 | 52.61 | \u221285.14 |\n\n**Servo solutions for the targets (degrees)**\n\n| Target | Coxa | Femur | Tibia |\n|---|---|---|---|\n| T1 | 118.00 | 70.00 | 58.00 |\n| T2 | 88.00 | 108.96 | 145.93 |\n| T3 | 101.02 | 65.02 | 58.02 |\n| T4 | unreachable | | |\n| T5 | unreachable | | |\n\n- **T4** is out of reach. It is 273 mm out from the coxa joint in the horizontal plane. Femur plus tibia can reach at most 210 mm beyond the 48 mm coxa link, i.e. 258 mm in total.\n- **T5** would need the coxa to turn about 47.0\u00b0, which is past its 41\u00b0 limit.\n\nThe script that produced the file is `/tmp/leg.py`, which is outside `out/`.",
  "ttft_ms": 2333,
  "type": "result",
  "duration_ms": 26883,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1717,
  "time_to_request_ms": 249,
  "first_content_frame_ms": 1718,
  "queued_turn_count": 0,
  "result_index": 0
 }
]