Caliber is a tool that generates and continuously updates AI context and configuration files for software repositories, including CLAUDE.md, AGENTS.md, and platform-specific rules. Development teams use it to keep coding agents aligned with the current codebase across tools such as Claude Code, Cursor, Codex, OpenCode, and GitHub Copilot. Its catalogue entries include skills, hooks, rules, instructions, and settings for configuring that workflow.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/caliber-ai-org/ai-setupnpx agentmods add skills/caliber-ai-org/ai-setup/writers-patternWrote 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/skills/caliber-ai-org/ai-setup/writers-pattern)<a href="https://agentmods.dev/skills/caliber-ai-org/ai-setup/writers-pattern"><img src="https://agentmods.dev/badge/skills/caliber-ai-org/ai-setup/writers-pattern/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/skills/caliber-ai-org/ai-setup/writers-pattern"><img src="https://agentmods.dev/badge/skills/caliber-ai-org/ai-setup/writers-pattern.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Rogue Agent · line 80 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00111 | $0.03775 |
| Opus 5.5 | $0.00044 | $0.01510 |
| Sonnet 5.5 | $0.00022 | $0.00755 |
| Haiku 4.5 | $0.00011 | $0.00378 |
Grade A, and why
writers-pattern 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.
How it starts
The opening of the file, as written. The whole thing — 268 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platform Writer Pattern
Critical
-
Every writer MUST:
- Export a single named function:
write<Platform>Config(config: <PlatformConfig>): string[] - Accept a platform-specific config interface defining what content to write
- Return
string[]of all written file paths (used by manifest and progress display) - Create parent directories with
fs.mkdirSync(dir, { recursive: true })before writing files - Wrap skill frontmatter exactly as shown in Step 4 (YAML between
---markers) - NOT modify files outside the intended platform directories (e.g., Claude writer only touches
.claude/,CLAUDE.md,.mcp.json)
- Export a single named function:
-
Integration point: Every writer MUST be imported and called in
src/writers/index.tswithin thewriteSetup()function. Missing this step means the writer will never execute. -
Validation before Step 1: Verify the platform name is unique (
ls src/writers/shows no<platform>/index.ts). If it exists, you are modifying, not adding.
Instructions
Step 1: Define the Platform Config Interface
Verify the platform name is unique (see Critical). Create src/writers/<platform>/index.ts.
At the top of the file, define a config interface that describes all content the writer accepts. The interface MUST include:
- A main markdown/text file (e.g.,
claudeMd,cursorrules,agentsMd,instructions) - Optional nested arrays:
rules,skills,mcpServers,instructionFiles, etc. - Each rule/skill/file has at minimum:
nameorfilename,content, and for skills,description
Example (matching GitHub Copilot pattern already in codebase):
interface CopilotConfig {
instructions: string; // Main content
instructionFiles?: Array<{ filename: string; content: string }>;
}
Validation: Confirm the interface property names match platform conventions (e.g., Claude uses claudeMd, Cursor uses cursorrules). Check existing writers: src/writers/claude/index.ts line 9, src/writers/cursor/index.ts line 9, src/writers/codex/index.ts line 5.
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 · 268 lines · 111 tokens per session scan A ea18f96e4f9e
writers-pattern is a skill published in the GitHub repository caliber-ai-org/ai-setup (1,309 stars, last pushed 29d ago), licensed MIT. It adds 111 tokens to every session and 3,775 once invoked, about $0.0004 per session on Opus 5.5. 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.
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