Kanvas: Instructions file for Codex

AGENTS.md

Kanvas AGENTS.md is an instructions file for Codex, OpenCode from XMihura/Kanvas. It costs 1,009 tokens per session, scanned A, original, MIT.

A set of instructions for using Obsidian Canvas files as visual task boards, with all changes made through a provided Python command-line tool.

In plain words
What is it for?
It helps assistants inspect the board, find available or blocked tasks, start work, and update task progress through commands.
Why use it?
It prevents direct edits that could break the board's workflow rules, such as invalid task transitions or dependency cycles.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is XMihura/Kanvas's own configuration. It tells Codex and OpenCode how to work on Kanvas itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Kanvas configures →

Reuse

Borrowing it

Nothing to install: this file belongs to XMihura/Kanvas. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/XMihura/Kanvas/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/XMihura/Kanvas

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 1,009 This file is loaded in full into every session.
When invoked 1,009 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.01009 $0.01009
Opus 5 $0.00504 $0.00504
Sonnet 5 $0.00202 $0.00202
Haiku 4.5 $0.00101 $0.00101

Measured 7d ago against content hash b0b5e0467296, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

Kanvas 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 7d 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 · 132 lines

How it starts

The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Canvas Workflow — Agent Instructions

This project uses Obsidian Canvas files as visual task boards. A Python CLI tool manages all board modifications.

CRITICAL RULE

NEVER edit .canvas files directly. All canvas modifications MUST go through the CLI tool:

python canvas-tool.py "<file>.canvas" <command> [args]

Direct JSON editing of .canvas files is forbidden. The CLI tool enforces workflow rules (valid transitions, cycle detection, blocked states) so you don't have to remember them.

Session Protocol

1. Start of session — read the board

python canvas-tool.py "Project.canvas" status

Review the board state. Run normalize if needed. Report ready tasks, blocked tasks, and any anomalies to the user.

2. Pick a task

python canvas-tool.py "Project.canvas" ready            # see what's available
python canvas-tool.py "Project.canvas" show <TASK-ID>    # read task details
python canvas-tool.py "Project.canvas" start <TASK-ID>   # begin work (red → orange)

If multiple tasks are ready, ask the user which to prioritize.

3. Work on the task

Execute the task. If you discover subtasks, propose them:

python canvas-tool.py "Project.canvas" propose Development "Subtask title" "Description" --depends-on DV-01

Update notes on your in-progress task:

python canvas-tool.py "Project.canvas" edit <TASK-ID> "Updated description with findings."

4. Finish the task

python canvas-tool.py "Project.canvas" finish <TASK-ID>   # orange → cyan

Tell the user what was done. Do NOT attempt to set the card green — only the human does that.

5. Repeat

After the human marks your task green, check for newly unblocked tasks:

python canvas-tool.py "Project.canvas" normalize
python canvas-tool.py "Project.canvas" ready

What you CAN do

  • Read the board: status, show, list, blocked, blocking, ready, dump
  • Normalize the board: normalize
  • Propose tasks: propose or batch (creates purple cards)
  • Propose groups: propose-group or batch
  • Start a task: start <ID> (red → orange)
  • Finish a task: finish <ID> (orange → cyan)
  • Pause a task: pause <ID> (orange → red)
  • Edit task text: edit <ID> "<text>" (only orange tasks)
  • Add dependencies: add-dep <FROM> <TO>

Read the full file on GitHub · 132 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. 7d ago First seen · 132 lines · 1,009 tokens per session scan A b0b5e0467296

Subscribe to this mod's changes

Kanvas AGENTS.md is an instructions file published in the GitHub repository XMihura/Kanvas (194 stars, last pushed 5mo ago), licensed MIT. It adds 1,009 tokens to every session, about $0.0050 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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