setup

setup is a skill for Claude Code from emaballarin/ccplugins. It costs 39 tokens per session (453 once invoked), scanned A, original, MIT.

A one-time setup tool for the mindfunnel plugin that creates shared instruction and memory files in the user's home directory. It also connects the relevant Claude Code and Codex files to that shared source.

In plain words
What is it for?
Use it when starting mindfunnel on a new machine or when its personal configuration directory is missing.
Why use it?
It gives the other mindfunnel tools the files they depend on without replacing files that already exist. This avoids rebuilding the setup manually on a new machine.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the dm42 plugin — 2 skills shipped together

Good fit Use it when starting mindfunnel on a new machine or when its personal configuration directory is missing.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add emaballarin/ccplugins
Claude Code
/plugin install dm42

Made for: Claude Code.

Or install dm42, the plugin that ships this one along with the rest of its 2 skills.

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 setup

README.md
[![agentmods](https://agentmods.dev/badge/skills/emaballarin/ccplugins/setup/github.svg)](https://agentmods.dev/skills/emaballarin/ccplugins/setup)
Your own site
<a href="https://agentmods.dev/skills/emaballarin/ccplugins/setup"><img src="https://agentmods.dev/badge/skills/emaballarin/ccplugins/setup/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 setup

Your own site · 80×15
<a href="https://agentmods.dev/skills/emaballarin/ccplugins/setup"><img src="https://agentmods.dev/badge/skills/emaballarin/ccplugins/setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 453 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00039 $0.00453
Opus 5.5 $0.00016 $0.00181
Sonnet 5.5 $0.00008 $0.00091
Haiku 4.5 $0.00004 $0.00045

Measured 9d ago against content hash 7662115e96ab, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

setup scanned grade A with 1 finding 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 9d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

1. **Check the tools**: `bash curl tar gzip patch make gcc g++ awk sed od which python3 sha256sum`, each with `command -v`, and Python 3.14 or later (the marketplace's floor): `python3 -c 'import sys; sys.exit(sys.versio
plugins/dm42dev/skills/setup/SKILL.md · 21 lines

What it actually says

/dm42:setup — build the DM42 emulator

Builds dm42sim into $DM42SIM_HOME, else $XDG_CACHE_HOME/dm42, else ~/.cache/dm42, one directory per pinned core. The first build downloads the core and compiles the Intel decimal library; later runs reuse both and finish quickly.

Steps

  1. Check the tools: bash curl tar gzip patch make gcc g++ awk sed od which python3 sha256sum, each with command -v, and Python 3.14 or later (the marketplace's floor): python3 -c 'import sys; sys.exit(sys.version_info < (3, 14))'. Done when all are present; otherwise name the missing ones with the package that provides them on this system, and stop — installing is the person's call.

  2. Build: bash "${CLAUDE_PLUGIN_ROOT}/scripts/build.sh", in the background when the harness supports it. The script stops at the first failure; its last line on success is the binary's path, preceded by smoke: OK. Add --rebuild only when the person asks for a clean build. Done when the exit status is 0 and bash "${CLAUDE_PLUGIN_ROOT}/scripts/build.sh" --path prints the same path.

  3. On failure, show the failing command's error and, for the decimal library, the tail of intel.log in the build directory. A smoke-test failure means this build does not behave like the device: report the failing checks, and keep the build unused.

  4. Report the binary's path, the pinned core (swissmicros/free42 3.3.10, commit a7c705e), and the smoke result. /dm42:rpn finds the binary by itself.

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. 9d ago Changed 7662115e96ab
  2. 10d ago Changed · -190 lines · -109 tokens per session cb825002c3b2
  3. 1mo ago Changed · -2 lines 8ca85240f8f8
  4. 1mo ago Changed · +24 lines · +20 tokens per session 8e8856aac6be
  5. 2mo ago First seen · 189 lines · 128 tokens per session scan A 97aeaf71cbfd

Subscribe to this mod's changes

setup is a skill published in the GitHub repository emaballarin/ccplugins (4 stars, last pushed 9d ago), licensed MIT. It adds 39 tokens to every session and 453 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

learn-from-fix

Capture Elixir/Ecto/LiveView lessons and Hex API rules. Use after corrections or when asked to document learning, record a lesson, prevent a fixed mistake, or remember package guidance with --library.

oliver-kriska/claude-elixir-phoenix · 46 tokens

recall

Recall prior work from past sessions — how a bug was fixed, what was decided, where a pattern lives. Use when asked 'have we done this before' or 'how did I fix X' in Elixir/Phoenix work. ccrider MCP when available, else git + solution docs.

oliver-kriska/claude-elixir-phoenix · 64 tokens

assigns-audit

Inspect LiveView socket assigns for memory bloat — missing temporaryassigns, unused assigns, unbounded lists needing streams, memory estimates. Use when LiveView memory grows or you need to add temporaryassigns.

oliver-kriska/claude-elixir-phoenix · 47 tokens

compound-docs

Searchable Elixir/Phoenix/Ecto solution documentation system with YAML frontmatter. Builds institutional knowledge from solved problems. Use when consulting past solutions before investigating new issues.

oliver-kriska/claude-elixir-phoenix · 38 tokens

context-anchoring

Manage per-feature living documents that capture decisions, constraints, and reasoning across AI sessions during active development. Scoped to feature-level work — design, implementation, bugfix, refactor — not for codebase-wide assessments or product-wide specifications (those define their own document lifecycles).…

techygarg/lattice · 147 tokens

learning-harvest

Manage the operational learnings lifecycle — load prior learnings to inform current work, harvest new patterns worth preserving, and keep the document tight over time. Provides a protocol for accumulating actionable patterns from practice that complement standards and defaults. Use when a workflow session completes…

techygarg/lattice · 114 tokens