| name | spawn-ori-eval |
| description | Run the self-contained Ori eval workflow, relay its one question at a time, and return the real eval results. |
| metadata | {"protocol":"ori-eval-spawn-v1","run_model":"openai/gpt-5.6-terra","judge_model":"openai/gpt-5.6-terra","harness":"pi"} |
Spawn Ori Eval
Use the executable that printed this skill. The executable owns the run
directory, task replay, production Ori subprocess, answer/error files, locking,
and summary accounting. Do not write an eval yourself and do not run model calls
outside it.
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From the repository root run:
ori-eval-system spawn prepare --request-file <file>
Use --request <text> only when the request is short. The defaults pin the
author harness to pi, the author model to openai/gpt-5.6-terra, and the
judge model to openai/gpt-5.6-terra.
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If it reports action-required, show the existing run summary and ask the
user whether to resume, archive and start fresh, or stop. Repeat prepare
with --existing resume, --existing archive, or --existing stop.
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Run:
ori-eval-system spawn run
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Read the JSON response. If its status is waiting, print context in an
ordinary message, including any table. Then ask with your own question UI
using prompt as one short sentence and the three labels in options,
keeping free-text Other. Do not put a markdown table in the question body.
Do not answer for the user.
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Pass the answer back without rewriting it:
ori-eval-system spawn answer --answer-file <file>
If the JSON has accepted: false, append nothing and do not restart Ori.
Respond to the clarification or complaint, then ask the same question again
through the question UI. Only a reply that answers the open question is
appended to the task prompt. If it has accepted: true, run
ori-eval-system spawn run explicitly; answers never launch the next paid
turn by themselves. Repeat steps 4 and 5 until status is completed.
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Relay the completed answer, including its results. Relay costTable in full
and the cheaperRerun line. Also relay attemptTotals. Tell the user the
scratch workspace is throwaway and may be moved into their repository if they
want to keep the eval.
Rules:
- Never edit the evaluated repository for this throwaway measurement.
- Never start more than one run process.
- Never bypass
ori auth, candidate approval, or any question emitted by Ori.
- Never invent a model, result, cost, duration, or answer.
- Do not substitute a harness or model unless the user explicitly requests it;
any override is persisted and displayed in the run state.
unknown cost is not zero.
- Never write "bakeoff" to the user. Replace it with "model comparison" every
time you relay, quote, or summarise Ori's text.
- A clarification request or complaint is not an answer. When
accepted is
false, append nothing, stay on the same question, and wait.