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Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Turn a long livestream transcript into one ordered learning page with the corrected key points

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

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.0056
Wall time
21s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Turn a long livestream transcript into one ordered learning page Input: `transcript.txt`, a synthetic transcript of a pottery livestream. Each line is `[time] SPEAKER: text`; time is `m:ss` or `mm:ss` in the first hour and `h:mm:ss` after. HOST is the presenter; `chat @name` lines are viewers. Rules: - A topic is introduced by a HOST line "Let's talk about <Topic>."; its start is the first such line, written hh:mm:ss. - A key point is a HOST line "Key point on <Topic>: <name> is <value>." (value is the text up to the final full stop). Later HOST corrections replace the value: "Correction: <name> is <new>, not <old>." or "Correction on <name>: it's <new>." - Ignore viewer chat lines, and everything from a HOST line starting "Quick word from our sponsor" through the next HOST line "Okay, back to it." (that line included). - Order: a HOST line "Before <B>, you need <A>." means A comes before B. Put topics in an order that respects every such line; when several topics could come next, take the one that started earliest. - Write `out/learning.json`: `{"order": [<topic>, ...], "starts": {"<topic>": "hh:mm:ss", ...}, "points": {"<topic>": {"<name>": "<value>", ...}, ...}}`. - Write `out/learning.md`: for each topic in order, a line `## <Topic> (hh:mm:ss)`, then one line `- <name>: <value>` per key point in the order the points were first stated. ## 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.

Turn a synthetic two-hour pottery livestream transcript into one study page. Topics come up out of teaching order and are revisited, prerequisites are stated in passing and must decide the order, the host corrects earlier key points in two different phrasings, viewers post wrong values in the same format, a sponsor segment plants a fake key point, and timestamps switch from m:ss to h:mm:ss after the first hour. 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: order starts corrections points_clean page

Setup notes: Batch 32 case te04-livestream-learning-page (offline, synthetic inputs, seed 3264420317). 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 0.19 (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-haiku-5.5: $0.005606. 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
$0.0056
Wall time
21s
Human step-ins
0
Turns
6
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on114,8383,999$0.0056

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: order starts corrections points_clean page
  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
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  "permission_denials": [],
  "terminal_reason": "completed",
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  "result": "I wrote `out/learning.json` and `out/learning.md`. The JSON parses and has six topics in the order Trimming, Bisque firing, Centering, Glaze firing, Glaze mixing, Wedging.\n\nChoices I made in applying the rules:\n\n- **Sponsor block:** I dropped everything from 37:22 to 43:10. That removes the \"Kiln safety\" topic and its key point, since its only lines fall inside the block.\n- **Ordering:** Wedging requires both Centering and Glaze mixing first. Glaze firing (45:28) started before Glaze mixing (54:19), so it comes first among the two.\n- **Repeated topic lines:** I used the first \"Let's talk about\" line for each topic's start, so Trimming is 00:04:04 and Centering is 00:18:34.\n- **Corrections:** Applied to foot ring depth (5 mm), wheel speed (about 150 rpm) and cooling rate (80 degrees an hour). Each key keeps its original position in the point order.\n- **Chat lines:** Ignored, including the viewer's \"4 hours?\" and \"10 minutes?\" guesses.\n\nI did not write anything under `ask/`.",
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 }
]

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