inference-sim
Official@inference-sim
Offers structured research experimentation, hypothesis formulation, and iterative technical documentation for complex repository analysis.
Agent Skills by inference-sim
Showing 9 vetted skills indexed across 1 GitHub repositories.
inference-sim_summarize-problem-context
Aggregate context from repositories, URLs, and web searches into a research document.
inference-sim_run-and-analyze
Execute experiment scripts, analyze output files, and classify hypothesis outcomes.
inference-sim_document-findings
Populates FINDINGS.md and updates HYPOTHESIS.md statuses from grep and read outputs.
inference-sim_formulate-hypothesis
Scan project code, tests, and documentation to formulate testable hypotheses.
inference-simhypothesis-test
Orchestrate hypothesis-driven experimentation with parallel or sequential agent execution.
inference-sim_scaffold-experiment
Generate run.sh, analyze.py, and FINDINGS.md templates for experiment scaffolding.
inference-sim_generate-ideas
Generate and iteratively refine research ideas with multi-model reviewer feedback.
inference-simreview-plan
Review Claude Code implementation plans via OpenAI-compatible LLM APIs.
inference-simresearch-ideas
Generate iteratively-reviewed research ideas from a problem statement.
Frequently Asked Questions About inference-sim
FAQPage SchemaWhat specific research tasks does inference-sim enable?▼
Inference-sim enables the systematic generation of research ideas, the formulation of testable hypotheses from existing codebases, and the execution of structured experiments. It facilitates the iterative review of implementation plans and the automated documentation of findings within project-specific markdown files.
Which technical personas benefit from using these capabilities?▼
Research engineers, technical leads, and software architects benefit from these capabilities. The system is designed for professionals who need to maintain rigorous experimental standards, track hypothesis outcomes across complex repositories, and ensure consistent documentation of technical findings during iterative development cycles.
What are the prerequisites for running these experiment modules?▼
Users require an environment capable of executing shell-based experiment templates and managing markdown documentation. The system relies on access to repository code, test suites, and documentation files to perform context aggregation and hypothesis formulation, alongside compatible endpoints for model-based review and feedback.