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.
npx agentmods add instructions/siviter-xyz/dot-agent/agents-mdgit clone --depth 1 https://github.com/siviter-xyz/dot-agentWrote 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/siviter-xyz/dot-agent/agents-md)<a href="https://agentmods.dev/instructions/siviter-xyz/dot-agent/agents-md"><img src="https://agentmods.dev/badge/instructions/siviter-xyz/dot-agent/agents-md.svg" alt="Measured on agentmods" 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 | $0.00544 | $0.00544 |
| Opus 5 | $0.00272 | $0.00272 |
| Sonnet 5 | $0.00109 | $0.00109 |
| Haiku 4.5 | $0.00054 | $0.00054 |
Grade A, and why
dot-agent AGENTS.md 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 6d 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 — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dot-agent Project Instructions
Skills authoring and best practices
- Prefer general, agent-harness and platform agnostic skills. If a skill must target a specific agent or environment, document this clearly in the SKILL.md frontmatter (e.g.
compatibility) and the skill’s README. Using a agent prefix also helps (e.g.,cursor-,claude-,win-, ...). - Follow the Agent Skills specification when adding or updating skills in this repo.
- Use the existing meta-skills when working in this repository:
create-skill– for creating or evolving skills with proper structure (frontmatter, progressive disclosure, references, scripts).create-agents-md– for adding project- or folder-specific AGENTS.md files in downstream repos.psi– for plan/spec/implement workflows when making non-trivial changes.semantic-git– for atomic commits using conventional commit typesand clear scopes.
- Each skill must have at least:
- A
SKILL.mdthat describes what it does and when to use it. - A documenting README in the skill directory when behavior or structure is non-trivial (e.g. scripts, workflows, or complex references).
- A
Scripts and tooling
- For skill scripts, prefer:
- uv scripts (PEP 723
# /// scriptmetadata +#!/usr/bin/env -S uv run --script) or - plain Bash for simple glue / shell workflows.
- uv scripts (PEP 723
- Scripts should aim to work cross-platform (Linux, macOS; avoid hard-coding platform-specific paths and shells where possible).
- When adding new Python-based scripts:
- Default to uv-managed scripts rather than ad-hoc virtualenvs.
- Keep dependencies explicit in the inline
scriptmetadata or ascripts/requirements.txtif a full project is needed.
Working in this repo
- Use skills from this repo to drive changes:
software-engineer+backend-engineer/frontend-engineerfor implementation guidance.code-reviewwhen reviewing or refactoring skills.
- Keep changes general and reusable by default; if something is project- or client-specific, prefer documenting it in that project’s own AGENTS.md rather than here.
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.
- 6d ago First seen · 39 lines · 544 tokens per session scan A ae8dcefb2795
dot-agent AGENTS.md is an instructions file published in the GitHub repository siviter-xyz/dot-agent (21 stars, last pushed 5mo ago), licensed MIT. It adds 544 tokens to every session, about $0.0027 per session on Opus 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.