context-prime

Materio: materials research interviews, supplied-corpus synthesis, lab feasibility, task execution and verified paper handoff.

6 skills

HPC pack: Slurm job arrays and sweeps through the clio-kit Slurm server, Lmod and Spack software environments, parallel HDF5 and MPI-IO, Darshan I/O analysis, and ChronoLog run records. The skills drive the cluster's own command-line tools; the clio-kit Slurm server needs one online launch to build its environment before it runs offline.

5 skills

Life-science pack: skills that query the RCSB Protein Data Bank, UniProtKB and PubChem over their public, key-free REST APIs with web_fetch, and stamp each answer with the source's entry revision or release. Every lookup needs network; offline the skills say the source is unreachable.

3 skills

Literature pack: verifies citations and resolves DOIs and arXiv IDs through the CiteNexus MCP server (cite-nexus-mcp 0.2.2, key-free Crossref, DataCite, Europe PMC and arXiv), with an offline extractor for BibTeX and Markdown and a web_fetch fallback. Adds a hypothesis workflow: cited grounding, independent council proposals, a testability ranking and the smallest experiment per hypothesis, ending at the operator's own choice. Extends arxiv-literature. Needs network for every lookup; the server needs one online launch to install.

2 skills

Decides the engineering approach for an intent in an interactive session: investigates, proposes two or three genuinely different approaches with trade-offs, recommends, lets the user decide, and writes the decision doc. Not a task-by-task plan; use sprint-plan. Not a multi-perspective debate; use design-council. Not product intent; use product-intent. Not a typed implementation handoff; use tech-spec.

1 skill

Searches arXiv, summarizes or compares papers, and builds a compact literature survey as citation-ready, source-linked paper cards, with BibTeX export and ID verification through the CiteNexus server when the literature pack is installed. Prefer the Researcher shadow agent for noisy multi-paper retrieval.

1 skill

Appends two or three short follow-up questions after a substantive answer to help users check key facts, probe the reasoning, and notice missing context

19 skills

Tenant-isolated AI teams that plan work, coordinate tasks, recall approved context, and return evidence-backed results

6 skills · 6 commands · 4 agents · 1 MCP server

Skill: add headroom-ai compress() to a Python or TypeScript app to cut LLM input tokens (tool outputs, logs, JSON, chat history). No API key.

1 skill

Up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your coding agent's context.

1 MCP server

Perform AI code review on Git diffs — supports workspace changes, branch ranges, and single commits with concurrent per-file analysis, codebase search, and deep context-aware review.

2 commands

Your code review partner. CodeRabbit provides external validation using a specialized AI architecture and 40+ integrated static analyzers—offering a different perspective that catches bugs, security vulnerabilities, logic errors, and edge cases. Context-aware analysis via AST parsing and codegraph relationships. Automatically incorporates CLAUDE.md and project coding guidelines into reviews. Useful after writing or modifying code, before commits, when implementing complex or security-sensitive logic, or when a second opinion would increase confidence in the changes. Returns specific findings with suggested fixes that can be applied immediately. Free to use.

2 skills · 1 command · 1 agent