Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/zkwasm/concord-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/plugins/zkwasm/concord-plugin/plugin)<a href="https://agentmods.dev/plugins/zkwasm/concord-plugin/plugin"><img src="https://agentmods.dev/badge/plugins/zkwasm/concord-plugin/plugin/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/plugins/zkwasm/concord-plugin/plugin"><img src="https://agentmods.dev/badge/plugins/zkwasm/concord-plugin/plugin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
concord scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
{
"name": "concord",
"description": "Join Concord rooms from Claude Code — multi-agent collaboration without writing integration code. Replaces the paste-prompt flow with /concord:join.",
"version": "0.7.0",
"author": {
"name": "Concord",
"url": "https://concord.fenginwind.com"
},
"homepage": "https://concord.fenginwind.com",
"repository": "https://github.com/zkwasm/concord-plugin",
"license": "MIT",
"mcpServers": {
"concord": {
"type": "stdio",
"command": "node",
"args": ["${CLAUDE_PLUGIN_ROOT}/server/dist/bundle.js"]
}
}
}
What it installs
The manifest is a name and a version. 1 skill, 4 commands, 1 MCP server travel with it, and installing the plugin installs all of them — 139 tokens a session between them. Each is measured on its own page, and each can be installed alone.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 20 lines scan A 508af443bf0c
concord is a plugin published in the GitHub repository zkwasm/concord-plugin (2 stars, last pushed 3mo ago), licensed MIT. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other plugins, from other repositories
security
Threat modeling, security architecture review, incident response, vulnerability management, and access and identity. Reviewer-class: blocking findings are not overrulable by the department under review.
data-analytics
Data governance, warehouse and semantic modeling, business intelligence, and AI/ML governance.
executive
Direction, capital and attention allocation, cross-functional arbitration, strategy validation, and the method for structuring the organization itself.
revenue
Outbound, sales enablement, revenue operations, pricing and packaging, activation, retention, and referrals.
markifact marketplace
Run Google Ads, Meta Ads, GA4, Shopify, and 50+ more platforms from Claude. 1000+ operations with human-in-the-loop on every write.
claude
Intent-to-implementation: from a goal, design docs, notes, or a mix, elicit and validate intent into a grounded 3-doc, then orchestrate dependency-aware parallel execution with right-sized review.