akashic-init

An initialization command for AkashicRecords, a knowledge-management system that uses RULE.md files to govern folders. It prepares the current directory and its subdirectories for that system.

In plain words
What is it for?
Use it to scan a directory tree, create or inherit RULE.md files, create or update README.md indexes, and validate the initial structure.
Why use it?
It establishes folder rules and README.md indexes before organized file management begins. It also identifies folders that need setup.

Command

Part of the akashicrecords plugin — 7 skills, 2 commands, 1 agent shipped together

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 commands/legacybridge-tech/claude-plugins/akashic-init
Clone the repo
git clone --depth 1 https://github.com/legacybridge-tech/claude-plugins

Or install akashicrecords, the plugin that ships this one along with the rest of its 7 skills, 2 commands, 1 agent.

Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 126 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00012 $0.00126
Opus 5 $0.00006 $0.00063
Sonnet 5 $0.00002 $0.00025
Haiku 4.5 $0.00001 $0.00013

Measured 2d ago against content hash 39dda914cccd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

akashic-init 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 2d 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.

akashicrecords/commands/akashic-init.md · 25 lines

What it actually says

Initialize AkashicRecords Governance

Mark the current directory and all subdirectories as following AkashicRecords governance rules.

What this does

  1. Scans current directory structure
  2. Identifies directories needing RULE.md or README.md
  3. Prompts user for initialization strategy
  4. Creates initial RULE.md (or inherits from parent)
  5. Creates/updates README.md with current contents
  6. Validates structure

Usage

/akashic-init

Invoke the governance agent to initialize directory governance.

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. 2d ago First seen · 25 lines · 12 tokens per session scan A 39dda914cccd

Subscribe to this mod's changes

akashic-init is a command published in the GitHub repository legacybridge-tech/claude-plugins (6 stars, last pushed 3mo ago), licensed MIT. It adds 12 tokens to every session and 126 once invoked, about $0.0001 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 2026-08-31.