Seal a run's inputs, record what it produced, bind every number in a manuscript to the run behind it as it is written, and verify the chain
Plugin results from marketplace reproducible-science in elliottower/reproducible-science. Commands read from the repo's manifest — yesterday.
This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.
resultsSeal a run's inputs before computing, record outputs after, bind manuscript claims to specific runs, and verify the hash chain. Use before launching any computation whose output will appear in a paper, after a run completes, while writing a sentence that states a number, when a number in a manuscrip
/results:results-checkDoes the results chain verify, and is every number in the manuscript bound to a run?
${CLAUDE_PLUGIN_ROOT}/hooks/unbound_numbers.py
Freeze a plan before running, seal a run's inputs, bind every number and quotation in a manuscript to what backs it, and check that each still resolves before submitting. Bundles prereg, citations, results and repro.
7 skills · 4 commands · hooks
Freeze a plan before you run it, and record what changed after
3 skills · 1 command · hooks
Check that quotations resolve in the sources they cite, and keep a library of the ones that do
1 skill · 1 command · hooks
Holds a Claude Code research session to its records: refuses an edit to a frozen plan, says when a manuscript or a run has no ledger behind it, and shows what the checks report.
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
15 skills · hooks
Run ruflo swarm agents on your own ruOS cloud desktops via the tenant-authenticated fleet MCP or per-tenant SSH; optional, removable
1 skill · 4 commands · 1 agent
HADS (Human-AI Document Standard) — semantic tagging convention for docs that work for both humans and AI models — plus the grounded-vault pattern for provenance-linked, drift-checked knowledge stores.
2 skills
Per-deal-and-packaging Commercial domain. v2.8.0 ships 8 skills: orchestrator + pricing-strategist (model picker + Van Westendorp WTP + packaging) + deal-desk (deal scorer + discount approval routing + redline) + partnerships-architect (5-tier classifier + joint GTM + revshare modeler) + channel-economics (cost-to-serve + ROI + mix optimizer) + commercial-policy (data-backed discount matrix + exception flow + linter) + rfp-responder (Shipley structured RFP/RFI/RFQ + win-theme + winrate predictor, context: fork) + commercial-forecaster (4Q-weighted bookings + cohort NRR/GRR + funnel-confidence with mandatory assumption disclosure). Hard rules: pricing outputs model+range (never a single number), deal outputs route to named human approver (never auto-approve), forecast outputs surface conversion assumption, RFP never invents claims for GAP requirements. 21 stdlib Python tools, 28+ reference docs. Distinct from business-growth (sales execution), c-level-advisor/cro-advisor (strategic), finance (close+report).
8 skills · 9 commands · 1 agent
Remove multi-vendor AI provenance marks from text, images, documents, and media. Bundles the remove-ai-marks and clean-user-facing-text skills.
2 skills · hooks
Comprehensive context engineering and harness engineering skills for production-grade AI agent systems: fundamentals, degradation patterns, compression, optimization, self-managed context (model-controlled live context editing), multi-agent coordination, long-horizon prompting (pseudo-formal task briefs for long-running and parallel agents), memory systems, tool design, filesystem context, hosted agents, evaluation, autonomous harnesses, self-improvement loops (RSI, meta-harnesses, evolutionary scaffold search), latent briefing (KV cache sharing between agents), project development, and cognitive architecture. Ships with a researcher operating system (rubrics, mechanism registry, claim provenance, run state machine, adversarial benchmarks, continuous loop).
19 skills
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