swarm: Skill for Claude Code

.skills/vault-init/SKILL.md

vault-init is a skill for Claude Code from swarm-ai-research/swarm. It costs 65 tokens per session (4,662 once invoked), scanned A, original, MIT.

A setup workflow for a research vault, which is a structured collection of notes and experiment records. It creates folders, templates, an index, starter notes, and optionally metadata for existing runs.

In plain words
What is it for?
Use it to initialize a vault, extend an existing one, install templates, seed starter notes, or add missing run metadata.
Why use it?
It gives a research project a consistent place and format for storing experiments, claims, and supporting evidence.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

This is swarm-ai-research/swarm's own configuration. It tells Claude Code how to work on swarm 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 swarm configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is - Validate: python scripts/validate-run.py --all.

Reuse

Borrowing it

Nothing to install: this file belongs to swarm-ai-research/swarm. 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/swarm-ai-research/swarm/main/.skills/vault-init/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/swarm-ai-research/swarm

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for vault-init

README.md
[![agentmods](https://agentmods.dev/badge/skills/swarm-ai-research/swarm/vault-init/github.svg)](https://agentmods.dev/skills/swarm-ai-research/swarm/vault-init)
Your own site
<a href="https://agentmods.dev/skills/swarm-ai-research/swarm/vault-init"><img src="https://agentmods.dev/badge/skills/swarm-ai-research/swarm/vault-init/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for vault-init

Your own site · 80×15
<a href="https://agentmods.dev/skills/swarm-ai-research/swarm/vault-init"><img src="https://agentmods.dev/badge/skills/swarm-ai-research/swarm/vault-init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,662 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 9
    Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
    Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
How audits are shown
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 $0.00065 $0.04662
Opus 5 $0.00032 $0.02331
Sonnet 5 $0.00013 $0.00932
Haiku 4.5 $0.00006 $0.00466

Measured 6d ago against content hash a221cd96f4d5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

vault-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 6d 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.

.skills/vault-init/SKILL.md · 689 lines

How it starts

The opening of the file, as written. The whole thing — 689 lines — stays where its author put it; the contents beside it link to each section on GitHub.

EXECUTE NOW

Target: $ARGUMENTS

Parse immediately:

  • If target is a path: use it as the vault root
  • If target is empty: use the current working directory
  • If target contains --backfill: also generate run.yaml for existing runs
  • If target contains --force: overwrite existing templates and index
  • If target contains --minimal: skip seeded content notes, only install templates

Execute steps 0 through 8 in order. Do not skip steps. Do not ask for confirmation between steps — execute the full sequence, then report.


Step 0: Detect Vault State

Read the target directory to determine what already exists.

Check for:

  • vault/ directory (has vault been initialized before?)
  • vault/_index.md (has the index been created?)
  • vault/templates/ (have templates been installed?)
  • runs/ directory (are there existing runs?)
  • schemas/ directory (have schemas been installed?)
  • run-index.yaml (has the run index been built?)

Decision tree:

  • If vault/_index.md exists AND --force not set → report "Vault already initialized" with a summary of what exists, then offer to run --backfill or --force
  • If vault/_index.md does not exist → proceed with full initialization
  • If --force is set → proceed, overwriting existing files

Store the state as context for remaining steps.


Step 1: Create Directory Structure

Create the full vault directory tree. Use mkdir -p to be idempotent.

vault/
├── experiments/          # one note per run (auto-generated)
├── claims/               # claim cards with evidence pointers
├── governance/           # governance mechanism notes
├── topologies/           # topology behavior notes
├── failures/             # named failure patterns from red-team
├── methods/              # reusable methodology notes
├── sweeps/               # cross-run sweep aggregations
└── templates/            # schema-enforced note templates

Also ensure these exist:

schemas/                  # JSON Schema files for validation
scripts/                  # automation tooling

Read the full file on GitHub · 689 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 6d ago First seen · 689 lines · 65 tokens per session scan A a221cd96f4d5

Subscribe to this mod's changes

vault-init is a skill published in the GitHub repository swarm-ai-research/swarm (42 stars, last pushed today), licensed MIT. It adds 65 tokens to every session and 4,662 once invoked, about $0.0003 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 2026-09-03.

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