swarm-ai-safety
Official@swarm-ai-safety
Simulate multi-agent systems and manage research knowledge vaults for distributional safety, emergent risk metrics, and statistical experiment validation.
Agent Skills by swarm-ai-safety
Showing 27 vetted skills indexed across 2 GitHub repositories.
rethink
Detect system drift and propose methodology updates for the SWARM research OS.
pipeline
Execute the complete SWARM synthesis pipeline for experiment runs.
next
Determine the next highest-priority action for the SWARM synthesis pipeline.
validate
Validate SWARM claims for provenance, statistical rigor, schema compliance, and boundary conditions.
seed
Initialize SWARM batch processing jobs by setting up queues and extraction tasks.
learn
Research AI safety topics and integrate findings into the SWARM knowledge vault.
update
Update claims with new evidence and lifecycle states.
graph
Analyze SWARM knowledge graph structure for orphan claims, clusters, and evidence chains.
extract
Extract structured claims and findings from SWARM experiment runs into a knowledge vault.
cross-link
Identify and articulate semantic connections between knowledge vault claims and topic maps.
remember
Record methodology friction and process corrections into the SWARM vault.
stats
Gather and display SWARM knowledge vault metrics and pipeline statuses.
swarm-safety
Simulate multi-agent AI systems to study distributional safety and emergent risks.
statistical-analysis
Perform pairwise t-tests, Cohen's d, and Bonferroni corrections on SWARM experiment CSV data.
plotting
Generate publication-quality plots from SWARM simulation sweep and time-series data.
parameter-sweep
Execute parameter grid sweeps across SWARM simulations to measure emergent risk metrics.
run-scenario
Execute SWARM simulation scenarios and export history.json and CSV metrics.
paper-writing
Scaffold markdown research papers from SWARM run data with methods and results tables.
regression-check
Re-run pytest suites and compare performance metrics against historical baselines.
verify
Run vault integrity checks for schema, evidence, wiki-links, and claims.
session-close
Summarize session changes, update memory logs, and commit code with Git.
run-query
Query run-index.yaml and vault claims for experiment metadata by tag, date, type, or claim.
vault-init
Initialize a SWARM Research OS vault with directory structure and templates.
sanity-check
Validate multi-agent simulation scenario configs with short runs and metric checks.
Frequently Asked Questions About swarm-ai-safety
FAQPage SchemaWhat specific research tasks are enabled by these capabilities?▼
These capabilities enable the execution of multi-agent simulation scenarios, statistical analysis of experiment data using t-tests and Cohen's d, and the management of research claims through a structured knowledge vault, including evidence tracking and semantic cross-linking of findings.
Which personas benefit from these research methodologies?▼
These capabilities are designed for AI safety researchers, computational social scientists, and experimentalists focused on distributional safety, emergent risk modeling, and the systematic documentation of multi-agent system behaviors and hypothesis testing.
What are the prerequisites for initializing a research environment?▼
To begin, users must initialize a Research OS vault to establish the required directory structure and templates. This environment relies on YAML-based run-indexing and structured CSV metric exports to maintain provenance and integrity across experiment lifecycles.