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/skarn-security/agent-guardWrote 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/skarn-security/agent-guard/recall)<a href="https://agentmods.dev/plugins/skarn-security/agent-guard/recall"><img src="https://agentmods.dev/badge/plugins/skarn-security/agent-guard/recall/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/skarn-security/agent-guard/recall"><img src="https://agentmods.dev/badge/plugins/skarn-security/agent-guard/recall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
skarn-recall 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 12d 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": "skarn-recall",
"version": "0.33.0",
"description": "Skill: reconstruct what you worked on from your AI coding sessions (recent, stats, redacted export). Reads session content, so it ships separately from skarn-guard. Backed by the Skarn session engine.",
"author": {
"name": "Skarn",
"url": "https://getskarn.com"
},
"homepage": "https://getskarn.com",
"repository": "https://github.com/skarn-security/agent-guard",
"license": "MIT",
"keywords": [
"sessions",
"recall",
"standup",
"timesheet",
"skills"
]
}
What it installs
The manifest is a name and a version. 1 skill travel with it, and installing the plugin installs all of them — 123 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.
- 12d ago Changed da8aa7a96a62
- 22d ago Changed 7df827b6cea5
- 1mo ago Changed a184c0c70cb0
- 1mo ago Changed 4c1456194de7
- 1mo ago Changed d5bfe292f220
- 1mo ago Changed 4c7b6a6a3d63
- 1mo ago First seen · 20 lines scan A 085ceef07ea8
skarn-recall is a plugin published in the GitHub repository skarn-security/agent-guard (36 stars, last pushed 12d 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 2026-08-30.
Other plugins, from other repositories
imprint
Your habits, imprinted on AI, plus judgment that adapts to you: when to act, when to check first, when the project rules win. A portable working profile across every agent. Powered by I-Lang v5.0.
imprint
Your habits, imprinted on AI. One extension replaces eleven skills: memory, compression, onboarding, code review, debugging, planning, progress tracking, testing, git workflow, SEO, and copywriting.
nowledge-community marketplace
Plugin marketplace listing 1 plugin: nowledge-mem.
nowledge-mem
Personal knowledge graph for Claude Code and Grok — remembers decisions, searches past work, captures sessions.
memory-optimization
Graph-backed memory and context optimization workflows with graphify first and document conversion helpers second.
gemini-faf-mcp
IANA-registered .faf project context for Gemini, with a deterministic AI-readiness score. Read, validate, score, and sync one source across GEMINI.md / CLAUDE.md / AGENTS.md. Run /faf:setup after install.