agent-skills AGENTS.md

Repository instructions for coding agents working on the Streamlit agent-skills project. The project contains a skill that locates Streamlit development guidance bundled with the installed Python package.

In plain words
What is it for?
Use them when changing the discovery script, adding or updating tests, editing documentation, or contributing skills in this repository.
Why use it?
They explain the repository layout, which files control discovery, and where tests and documentation belong. They also clarify that new Streamlit skill content should be contributed to Streamlit itself.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/streamlit/agent-skills/agents-md
Clone the repo
git clone --depth 1 https://github.com/streamlit/agent-skills

Made for: Codex, OpenCode.

Per session 880 This file is loaded in full into every session.
When invoked 880 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00880 $0.00880
Opus 5 $0.00440 $0.00440
Sonnet 5 $0.00176 $0.00176
Haiku 4.5 $0.00088 $0.00088

Measured 3d ago against content hash f0c66544dc87, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-skills 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 3d 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.

AGENTS.md · 43 lines

How it starts

The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file provides guidance to AI coding agents (Claude Code, Cursor, Copilot, etc.) when working with code in this repository.

Repository overview

This repository contains a single meta-skill that teaches AI agents how to discover Streamlit development skills bundled inside the Streamlit pip package (1.57+).

The actual skill content (dashboards, themes, layouts, session state, custom components, etc.) now ships with Streamlit itself. This repo provides the entry point that bootstraps that discovery — new skill content should be contributed upstream to the Streamlit repository, not added here.

Key files:

  • developing-with-streamlit/SKILL.md — Meta-skill that locates and loads bundled Streamlit skills
  • developing-with-streamlit/scripts/discover.py — The actual contract implementation (interpreter detection, package-path lookup, fallback exit codes); edit this when changing discovery behavior
  • tests/discovery/test_discovery.py — Pytest suite that exercises every documented codepath in discover.py on Linux + Windows; add a test here when adding a new branch
  • README.md — Human-readable documentation and install instructions

Meta-skill contract

The meta-skill at developing-with-streamlit/SKILL.md resolves the bundled routing skill by:

  1. Detecting the active Python interpreter, in priority order: $VIRTUAL_ENV./.venv../.venv<git-root>/.venv$CONDA_PREFIXpipenv (if Pipfile present) → poetry (if poetry.lock present) → pdm (if pdm.lock present) → uv (if uv.lock present) → system python3 / python.
  2. Running python -c "import streamlit; print(streamlit.__path__[0])" to locate the installed package.
  3. Loading <streamlit_path>/.agents/skills/developing-with-streamlit/SKILL.md.
  4. Falling back to pip install streamlit when missing, or https://docs.streamlit.io/llms-full.txt when the installed version predates bundled skills.

When editing the meta-skill, preserve this contract. Changes that alter interpreter detection order, the package-path lookup, or the fallback behavior should be explicit and reviewed.

Read the full file on GitHub · 43 lines

Changes

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.

  1. 3d ago First seen · 43 lines · 880 tokens per session scan A f0c66544dc87

Subscribe to this mod's changes

agent-skills AGENTS.md is an instructions file published in the GitHub repository streamlit/agent-skills (224 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 880 tokens to every session, about $0.0044 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.

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