openclaw / openclaw/shellbench
Guidance for a reproducible ClawBench task-authoring comparison
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- Dominant language
- Python
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- 139
- Forks
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- Avg merge
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- Merged PRs (30d)
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Description
Context
I am building a reproducible comparison of a native, non-proxy Codex control
against deepseek/deepseek-v4-flash-0731 in two CLI harnesses. The first two
checks create office artifacts; the final check should author and validate a
complete task in the OpenClaw/ClawBench ecosystem. Every arm receives identical
bytes and we record deterministic score, blind quality score, wall time, token
usage, cost, failures, and interventions over at least three matched runs.
The infrastructure is adapted from
https://github.com/lakshitsachdeva/deepseek-trial, but the task/data and final
results will be new.
Proposed Check 3
Have each arm author a complete ClawBench task package from one frozen seed:
- working title: Background Task Ledger Export Repair
- target: Tier 3
repo/multi_tool - fixture: a small Python task-ledger exporter with independent normalization,
terminal-state filtering, and completion-deduplication bugs - expected agent trajectory: inspect multiple files, implement fixes, run the
deterministic verifier, and report the result - required output: canonical task YAML, asset pack, tests/verifier, and any
manifest entry required by the current public pipeline - scoring: deterministic completion first; an LLM judge must never rescue a
deterministic failure
This makes the measured work task authoring—not merely replaying a contaminated
public task—and gives all three arms the same frozen OpenClaw/ClawBench source
snapshot.
Guidance requested
Could a maintainer confirm:
- the current canonical task/asset-pack schema and directory layout;
- the exact validation command we should treat as official;
- whether there is an oracle/reference-solution check for newly authored tasks;
- the OpenClaw and ClawBench versions/commits that should be pinned together;
- whether this proposed seed is useful, or what seed would better exercise an
end-to-end OpenClaw workflow without duplicating a public Core v1 task; and - whether three runs per arm is adequate for a small study, or whether your
current methodology requires a different minimum.
I will keep the final source lock ready: false until these details are fixed
and will record the maintainer response and exact commit in the result package.
If an issue is not the right coordination channel, please point me to the
preferred OpenClaw/ClawBench contact.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No source files or validation command are identified in the issue. Start by locating the current public OpenClaw/ClawBench task schema, asset-pack layout, and validation entry point; done means maintainers confirm the pinned versions, oracle check, seed suitability, and run-count methodology.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, testing-qa
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100