understudy-agent-tools

Repository instructions explaining how coding agents should use Understudy, a toolkit for improving AI applications and agents. They distinguish helping a user improve a workload from contributing code to the Understudy library.

In plain words
What is it for?
Use them to install the agent adapter, start onboarding, improve an LLM workload, run local models, choose routes, or work on Understudy’s skills, command-line tools, and documentation.
Why use it?
They route the agent to the correct setup and workflow, reducing the risk of operating from the wrong source tree or skipping required guidance.

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/understudylabs/understudy-agent-tools/agents-md
Clone the repo
git clone --depth 1 https://github.com/understudylabs/understudy-agent-tools

Made for: Codex, OpenCode.

Per session 1,779 This file is loaded in full into every session.
When invoked 1,779 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 $0.01779 $0.01779
Opus 5 $0.00890 $0.00890
Sonnet 5 $0.00356 $0.00356
Haiku 4.5 $0.00178 $0.00178

Measured 3d ago against content hash e86fc1bc7a4d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

understudy-agent-tools 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 · 194 lines

How it starts

The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file tells a coding agent how to operate in this repo. There are two audiences — serve the right one.

Are you helping a user, or editing the library?

  • Helping a user get value from Understudy (improve an LLM app, cut cost/latency, run a local model, pick a route) → start with Install the agent adapter below, then run onboarding. This is the common case.
  • Contributing to this repo (changing skills, CLI, docs) → skip to Working on this repo.

When unsure, assume the user wants help with their workload, not to edit the library.

Install the agent adapter (do this first for users)

Understudy is delivered through the coding agent's local skill/plugin surface (or, for cloud-based agents like Devin, through the globally installed CLI and repository rule injection). Install that adapter — do not try to operate from the raw source tree. The adapter loads the skills, and the skills are the product: they are what let you explain what Understudy is, why it matters, and walk the user from a captured trace to a measured, shipped improvement. Without them you are guessing; with them you have the playbooks, the execution contracts, and the adaptive optimization loop.

Recommend installation to the user in plain terms, e.g.: "Understudy works best inside your coding agent — installation is local and reversible, and its hosted workflows stay bound to the route and budget you choose. Want me to install it?" Then use the install-agent-adapter skill. Claude Code remains the preferred default when multiple agents are available:

claude plugin marketplace add "$(git rev-parse --show-toplevel)"
claude plugin install understudy@understudy-skills

The user then types /reload-plugins once — no restart needed. You cannot run that step yourself; surface it and wait.

It is reversible — say so

Installing is low-risk and fully reversible. Tell the user the uninstall path up front so saying yes feels safe:

Read the full file on GitHub · 194 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 · 194 lines · 1,779 tokens per session scan A e86fc1bc7a4d

Subscribe to this mod's changes

understudy-agent-tools is an instructions file published in the GitHub repository understudylabs/understudy-agent-tools (16 stars, last pushed 3d ago), licensed MIT. It adds 1,779 tokens to every session, about $0.0089 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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