Agent_View_Controller-AVC AGENTS.md

Instructions for using AVC, a visual tool that turns JSON data into interactive screens for human decisions. It can show plans that a person may confirm, edit, reorder or cancel.

In plain words
What is it for?
It helps present execution plans, multi-module architecture changes, multi-file refactoring plans and deployment sequences for human approval, then read the approved plan and cancellation status.
Why use it?
Plain terminal output is awkward when a person must approve or revise a multi-step plan. AVC provides a screen for reviewing the proposed steps and returns the person's decision.

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/study8677/agent_view_controller-avc/agents-md
Clone the repo
git clone --depth 1 https://github.com/study8677/Agent_View_Controller-AVC

Made for: Codex, OpenCode.

Per session 1,044 This file is loaded in full into every session.
When invoked 1,044 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 $0.01044 $0.01044
Opus 5 $0.00522 $0.00522
Sonnet 5 $0.00209 $0.00209
Haiku 4.5 $0.00104 $0.00104

Measured yesterday against content hash 201b89f0ab72, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Agent_View_Controller-AVC 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 yesterday.

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 · 129 lines

How it starts

The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AVC Integration Guide for AI Agents

What is AVC?

AVC (Agent View Controller) is a visual interaction tool installed on this system. It transforms JSON data into interactive visual UIs for human decision-making.

Binary location: avc (in PATH) or ./avc (project root)

When to Use AVC

Use AVC instead of printing plain text when you need human approval for:

  • Execution plans with more than 3 steps
  • Architecture changes involving multiple modules
  • Multi-file refactoring plans
  • Deployment sequences that need human ordering

How to Use

Construct a JSON object following the schema below, then pipe it to avc:

echo '{"view":"plan","title":"Your Plan Title","editable":true,"data":{"steps":[{"id":1,"label":"Step description","status":"pending"}]}}' | avc

Important Behavior

  1. The avc command blocks until the human clicks Confirm or Cancel
  2. stdout contains the modified JSON (human may have reordered, edited, or removed steps)
  3. Exit code 0 = confirmed, exit code 130 = cancelled
  4. Parse the returned JSON to get the human-approved plan
  5. Token threshold: If the input token count ≤ 3000 (default), AVC will pass-through — it outputs the original JSON to stdout and exits with code 0 without opening a window. This avoids interrupting the human for short content.

Token Threshold

AVC has a built-in token threshold (default: 3000 tokens). When the content is short, AVC skips the WebView and passes through directly.

How it works:

  • If the JSON contains a token_count field, AVC uses that value
  • Otherwise, AVC estimates tokens from the JSON byte length (bytes / 3)
  • If the token count ≤ threshold, AVC passes through without opening a window

To always show the WebView (bypass threshold), use --no-threshold:

echo '<json>' | avc --no-threshold

To set a custom threshold:

echo '<json>' | avc --threshold=5000

To include token count in JSON (recommended for accuracy):

{
  "view": "plan",
  "title": "Your Plan",
  "token_count": 4500,
  "data": { "steps": [...] }
}

Read the full file on GitHub · 129 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. yesterday First seen · 129 lines · 1,044 tokens per session scan A 201b89f0ab72

Subscribe to this mod's changes

Agent_View_Controller-AVC AGENTS.md is an instructions file published in the GitHub repository study8677/Agent_View_Controller-AVC (68 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 1,044 tokens to every session, about $0.0052 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.