StatsClaw
Official@statsclaw · United States of America
Collaborative AI for Statistical Packages
Agent Skills by StatsClaw
Showing 15 vetted skills indexed across 1 GitHub repositories.
statsclawprofile-detection
Scan repository markers to select language profiles for StatsClaw workflows.
statsclawprivacy-scrub
Genericize identifiers, file paths, and metadata in knowledge entries.
statsclawstatsclaw-protocol
Orchestrate specialized AI agents for statistical package development workflows.
statsclawhandoff
Govern leader-mediated artifact handoffs between StatsClaw agent pipelines.
statsclawworkspace-sync
Sync non-code workflow artifacts to a centralized GitHub workspace repository.
statsclawmailbox
Enforce an append-only shared mailbox for standardized agent team communication.
statsclawprogress-bar
Render text-based progress indicators for StatsClaw statistical package workflows.
statsclawsimulation-study
Automate Monte Carlo simulation studies evaluating statistical estimator performance.
statsclawbrain-sync
Coordinate consent-gated knowledge sharing and automated PR creation for StatsClaw workflows.
statsclawisolation
Enforce filesystem and information isolation between AI agent pipelines for statistical software validation.
statsclawcontribute
Extract session insights from statistical package workflows for shared knowledge base contributions.
statsclawattribution
Remove bot co-author trailers and tool footers from AI-generated git commits.
statsclawcredential-setup
Detect, configure, and verify GitHub authentication credentials for StatsClaw workflows.
statsclawsimplified-workflow
Run a 4-step pipeline for small routine code changes.
statsclawissue-patrol
Scan, triage, and resolve open GitHub issues with automated pull requests.
Frequently Asked Questions About StatsClaw
FAQPage SchemaWhat specific tasks can StatsClaw perform for statistical developers?▼
StatsClaw enables the execution of Monte Carlo simulation studies, automated triage of repository issues, and the synchronization of session insights. It manages the lifecycle of statistical package development by enforcing filesystem isolation between pipelines and governing artifact handoffs between specialized development processes.
Which personas benefit most from using StatsClaw?▼
StatsClaw is designed for statistical software engineers, data scientists, and research developers who maintain complex packages. It is particularly useful for teams managing high-volume repository issues and those requiring rigorous validation of statistical estimators through repeated simulation studies.
What are the prerequisites for deploying StatsClaw in a repository?▼
Deployment requires active GitHub authentication credentials and a repository structure compatible with StatsClaw's profile detection markers. Users must configure credential verification to enable the system to interact with GitHub repositories, manage pull requests, and sync workspace artifacts effectively.