Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add xingwudao/open-xquant --skill compare-experimentsgit clone --depth 1 https://github.com/xingwudao/open-xquantWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xingwudao/open-xquant/compare-experiments)<a href="https://agentmods.dev/skills/xingwudao/open-xquant/compare-experiments"><img src="https://agentmods.dev/badge/skills/xingwudao/open-xquant/compare-experiments/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xingwudao/open-xquant/compare-experiments"><img src="https://agentmods.dev/badge/skills/xingwudao/open-xquant/compare-experiments.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00014 | $0.00913 |
| Opus 5.5 | $0.00006 | $0.00365 |
| Sonnet 5.5 | $0.00003 | $0.00183 |
| Haiku 4.5 | $0.00001 | $0.00091 |
Grade A, and why
compare-experiments scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Experiment Comparator
Use this skill when the user asks to compare two completed runs. The comparison
is cross-experiment metadata, so do not write outputs inside either run
directory. Resolve the comparison output root from .open-xquant/workspace.yaml
when it exists: use paths.comparisons_dir for the comparison directory root
and paths.comparison_registry for the summary registry. Fall back to
comparisons/ and comparisons/comparisons.jsonl only when no workspace config
value is present.
Do not use this skill in a version-governed workspace. Stop before reading run
artifacts or writing comparison outputs and route the request to
compare-strategy-versions, including when the user only says "compare two
experiments". The version-aware comparator must validate each candidate against
its claimed version manifest and backtest phase.
Classify the workspace exactly as the CLI does: it is version-governed if and
only if workflow.layout == version_governed or the paths.versions_dir key
is present. Otherwise it is legacy, even when .open-xquant/workspace.yaml
exists. Use this legacy comparator only in the latter case.
Preconditions
Both runs must contain:
strategy_spec.yamlmetrics.jsonequity_curve.csvexecution_assumptions.jsonresearch_bias_audit.jsonreproducibility_audit.json
If a run lacks metrics.json, say that the experiment has not completed a
backtest and cannot be compared yet.
If either run lacks audit or execution-assumption artifacts, stop and explain
that audited comparison requires those artifacts before naming winners or
writing spec-impact conclusions. If an audit contains fatal findings, do not
present that run as comparable to an audited candidate without making the audit
failure the primary result.
Workflow
- Read both
strategy_spec.yamlfiles and generatespec_diff.yaml.- Compare fields recursively.
- Include path, run A value, run B value, and likely impact.
- Read
execution_assumptions.jsonand both audit artifacts for each run.- Verify execution assumptions are comparable before interpreting metric differences.
- Treat reproducibility or research-bias failures as blockers for winner-style conclusions.
- Read both
metrics.jsonfiles and generatemetrics_comparison.json.- Include key metrics for each run.
- Include deltas and winners by return, Sharpe, and drawdown where present.
- Generate figures under
<comparisons_dir>/<comparison_id>/figures/.equity_overlay.pngdrawdown_overlay.pngmetrics_bar.pngDo not leavefigures/empty. If no figure will be generated, do not create the directory.
- Write
comparison_report.md.- Explain which spec differences plausibly drove the metric differences.
- Do not claim causality when the evidence only supports association.
- Append a summary row to
<comparison_registry>.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 103 lines · 14 tokens per session scan A e14714ec6ef4
compare-experiments is a skill published in the GitHub repository xingwudao/open-xquant (149 stars, last pushed 15d ago), licensed MIT. It adds 14 tokens to every session and 913 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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