By jasonm4130
Configurable adversarial panel review for any artefact — plans, code, design docs, prose, model outputs. Auto-selects panel personas by artefact type, dispatches in parallel, walks critiques convergence-prioritised.
A Claude Code plugin marketplace hosting multiple independent plugins. Install the whole marketplace with one command, then pick which plugins to enable.
/plugin marketplace add jasonm4130/claude-skills
| Plugin | Description | Install command |
|---|---|---|
adversarial-agents | Configurable adversarial panel review for any artefact | /plugin install adversarial-agents@jasonm4130-claude-skills |
deep-research | Multi-source research via parallel sub-agents and synthesis | /plugin install deep-research@jasonm4130-claude-skills |
session-retro | Interactive session retrospectives that capture learnings to memory | /plugin install session-retro@jasonm4130-claude-skills |
handoff | Context-fill-triggered handoff skill that auto-loads on next session | /plugin install handoff@jasonm4130-claude-skills |
For full details on each plugin, see its own README:
plugins/adversarial-agents/README.mdplugins/deep-research/README.mdplugins/session-retro/README.mdplugins/handoff/README.mdNote for handoff users: The handoff plugin requires an additional
statusLinewiring step in your~/.claude/settings.json— seeplugins/handoff/README.mdfor the snippet.
adversarial-agentsConfigurable adversarial panel review for any artefact — plans, code, design docs, prose, model outputs.
[CONVERGED] overlap promotion — critiques surfaced by 2+ personas walked firstTrigger phrases include grill me, stress-test this, red-team, adversarial review, panel critique, find holes.
deep-researchMulti-source research with DAG-planned dispatch, cost-aware model selection (Haiku critics + Sonnet synthesis + Opus orchestrator), and three-pass synthesis (critic → citation-quality judge → final-judge).
Follows the lead-researcher → parallel sub-agents → synthesis pattern from Anthropic's multi-agent research system, extended with 2025–26 patterns (plan-as-DAG, role-separated critic vs judge, asymmetric models).
This plugin uses the Claude Code plugin marketplace mechanism. Add to your ~/.claude/settings.json:
{
"extraKnownMarketplaces": {
"jasonm4130-claude-skills": {
"source": { "source": "github", "repo": "jasonm4130/claude-skills" }
}
},
"enabledPlugins": {
"jm-skills@jasonm4130-claude-skills": true
}
}
Then run /plugins in Claude Code to sync. Skills will be invokable as jm-skills:adversarial-agents and jm-skills:deep-research, plus by their natural trigger phrases.
.claude-plugin/plugin.json # plugin manifest
skills/
adversarial-agents/
SKILL.md # skill definition + frontmatter
personas/
yagni.md, premortem.md, hidden_assumptions.md # plan panel
saboteur.md, new_hire.md, security_auditor.md # code panel
deep-research/
SKILL.md
MIT — see LICENSE.
adversarial-agents was prompted by Matt Pocock's grill-me skill. The panel-of-personas + severity-promotion pattern draws on Alireza Rezvani's adversarial-reviewer and zscole's adversarial-spec. The full research synthesis behind the design decisions lives in the originating dotfiles plan (docs/plans/2026-05-16-skills-overhaul-research.md).
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npx claudepluginhub jasonm4130/claude-skills --plugin adversarial-agentsInteractive session retrospectives — deterministic Stop/PreCompact triggers, diff-driven interview, native memory entries. No external services.
Context-fill-triggered handoff skill — writes a structured resume doc when context fills, auto-loads it on next session.
Interactive session retrospectives — deterministic Stop/PreCompact triggers, diff-driven interview, native memory entries. No external services.
Complete AI coding workflow system. Self-correcting memory + persistent FTS5-indexed research wikis + auto-research loop + multi-LLM council on a single SQLite store. 33 skills, 8 agents, 22 commands, 37 hook scripts across 24 events. Cross-agent via SkillKit.
Make your AI agent code with your project's architecture, rules, and decisions.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Build and maintain an LLM-curated personal knowledge base in your project — Andrej Karpathy's LLM Wiki pattern, designed to scale to thousands of pages without becoming a context bottleneck. Now with an optional compiled graph layer for typed, provenance-backed relationships.
Connect to Atlassian products including Jira and Confluence. Search and create issues, access documentation, manage sprints, and integrate your development workflow with Atlassian's collaboration tools.
AI-powered wiki generator for code repositories. Generates comprehensive, Mermaid-rich documentation with dark-mode VitePress sites, onboarding guides, deep research, and source citations. Inspired by OpenDeepWiki and deepwiki-open.