Borrowing it
Nothing to install: this file belongs to devrimcavusoglu/skern. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/devrimcavusoglu/skern/main/AGENTS.mdgit clone --depth 1 https://github.com/devrimcavusoglu/skernWrote 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/instructions/devrimcavusoglu/skern/agents-md)<a href="https://agentmods.dev/instructions/devrimcavusoglu/skern/agents-md"><img src="https://agentmods.dev/badge/instructions/devrimcavusoglu/skern/agents-md/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/instructions/devrimcavusoglu/skern/agents-md"><img src="https://agentmods.dev/badge/instructions/devrimcavusoglu/skern/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.04349 | $0.04349 |
| Opus 5.5 | $0.01740 | $0.01740 |
| Sonnet 5.5 | $0.00870 | $0.00870 |
| Haiku 4.5 | $0.00435 | $0.00435 |
Grade B, and why
skern AGENTS.md scanned grade B with 1 finding 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 2mo 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.
Enumerates other installed skillsmediumAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
| Per-platform capacity (project scope) | Count in the platform's project skills dir (e.g. `.claude/skills/`) | Warn at >= 20 | How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Skern Development Guide
Conventions, architecture, and design decisions for agents working in this repo. Human contributor setup — the full build/test matrix, directory tree, and dependency list — lives in docs/contributing/development.md. Release history lives in CHANGELOG.md; neither is restated here.
Project Overview
Skern is a minimal, agent-first CLI for managing Agent Skills across agentic
development platforms. It follows the Agent Skills open standard
(agentskills.io) and uses SKILL.md files with YAML
frontmatter as the canonical format.
Written in Go 1.25+. Latest release v0.4.0; main carries unreleased
work (see the [Unreleased] section of the CHANGELOG).
Scope
The registry is the center of gravity. Skern's value is being the single
cross-platform source of truth for skills: one SKILL.md per skill, stored
once, managed through skern regardless of which agent is running. Registry
commands (create, import, edit, list, search, show, validate,
version, diff, recommend, remove) are the primary surface, and
skern init --instructions exists so an agent can be told to reach for skern
directly instead of hunting through platform directories.
Platform install/uninstall is first-class and stays. Copying skills out to
native platform directories serves real cases the registry alone does not:
native progressive disclosure, sandboxed agents that cannot shell out to
skern, and one-shot migration from an existing .claude/skills/. Adapters are
maintained and extended, and adapter bugs are ordinary product bugs — they are
just not the headline drive. The skern skill command tree encodes this split
directly via two cobra groups: Registry commands and Platform commands
(internal/cli/skill.go).
When proposing features, weigh them against the registry thesis first. New work that only makes sense as a per-platform copy needs a use case from the list above.
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.
- 2mo ago First seen · 376 lines · 4,349 tokens per session scan B 87464af57700
skern AGENTS.md is an instructions file published in the GitHub repository devrimcavusoglu/skern (7 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 4,349 tokens to every session, about $0.0174 per session on Opus 5.5. A static security scan graded it B with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
skern AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| skern AGENTS.mddevrimcavusoglu/skern | Instructions file | 7 | 2mo ago | Apache-2.0 | B | 4,349 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |