claude-mods

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A comprehensive extension toolkit that transforms Claude Code into a specialized development powerhouse.

claude-mods is a production-ready plugin that extends Claude Code with 96 specialized skills, 3 expert agents, 13 output styles, 11 hooks, and modern CLI tools designed for real-world development workflows. Whether you're debugging React hooks, optimizing PostgreSQL queries, or building production CLI applications, this toolkit equips Claude with the domain expertise and procedural knowledge to work at expert level across multiple technology stacks.

Built on the Agent Skills specification (an open standard backed by Anthropic, Vercel, Google, Microsoft, and 40+ agent platforms), claude-mods fills critical gaps in Claude Code's capabilities: persistent session state that survives across machines, on-demand expert knowledge for specialized domains, token-efficient modern CLI tools (10-100x faster than traditional alternatives), and proven workflow patterns for TDD, code review, and feature development. The toolkit implements Anthropic's recommended patterns for long-running agents, ensuring your development context never vanishes when sessions end.

From Python async patterns to Rust ownership models, from AWS Fargate deployments to Craft CMS development - claude-mods provides the specialized knowledge and tools that transform Claude from a general-purpose assistant into a domain expert who understands your stack, remembers your workflow, and ships production code.

3 agents. 96 skills. 13 styles. 11 hooks. 8 rules. One install.

Recent Updates

v3.4.0 (June 2026)

• 📊 r-ops skill — the set's first data-science skill: a tidyverse-first, current-best-practice reference for modern R (2024+). SKILL.md routes an import → tidy → transform → visualize → model → communicate workflow across 9 reference files (~115 KB) — tidyverse-core, import-io, strings-dates-factors, visualization, iteration-functional, modeling-stats, data-table, time-series, workflow-tooling. Leads with current idioms (native |>, dplyr .by=, the \(x) lambda, across(), list_rbind, slice_*, tidymodels, the tidyverts tsibble/fable stack, Quarto + renv) and names base R / data.table where they win. Ships a 43-assertion offline self-test plus a check-r-facts.py §7 staleness verifier (--offline asserts every catalogued CRAN package is still named in the prose and the currency note carries a year; --live resolves each package on CRAN) so the modern-stack claim is machine-enforced, not asserted. Salvaged and freshened from the stale stacked PR #6 (which also duplicated the already-shipped supply-chain-defense), re-landed clean off current main.

v3.3.0 (June 2026)

• 🔁 loop-ops skill — the outer-loop design discipline: how to design and safely run scheduled, autonomous agent loops — the orchestration layer above iterate (which drives a single inner run). Its backbone is a graduated-autonomy risk ladder (L1 report → L2 assisted → L3 unattended) mapped onto Claude Code's actual permission model, so a loop only ever gets the authority it has earned — anchored by the rule that a scheduler invokes claude -p, never a session spawning ungated children. Ships a 13-pattern morphology — trigger (cadence · event-driven Channels · /goal run-to-completion) × posture (L1–L3) × locus (connector→cloud routine · local→Desktop task) — plus a STATE/run-log/budget spine, multi-loop coordination, and a kill switch. Three tools do the work: loop-scaffold seeds a near-ready loop, loop-check refuses a green light on an unbounded scope / missing gate / undefined escalation, and loop-estimate gives caching-aware cost/month before you commit to a cadence. Composes fleet-worker (spawn) and fleet-ops (land).