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.
npx agentmods add skills/packmindhub/packmind/packmind-create-commandnpx skills add PackmindHub/packmind --skill packmind-create-commandgit clone --depth 1 https://github.com/PackmindHub/packmindWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00047 | $0.02824 |
| Opus 5 | $0.00023 | $0.01412 |
| Sonnet 5 | $0.00009 | $0.00565 |
| Haiku 4.5 | $0.00005 | $0.00282 |
Grade A, and why
packmind-create-command 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.
How it starts
The opening of the file, as written. The whole thing — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Command Creator
This skill provides a complete walkthrough for creating reusable commands via the Packmind CLI.
About Commands
Commands are structured, multi-step workflows that capture repeatable tasks, recipes, and automation patterns. They help teams standardize common development workflows and enable GitLab Duo to execute complex tasks consistently.
What Commands Provide
- Multi-step workflows - Structured sequences of actions to accomplish a task
- Context validation - Checkpoints to ensure requirements are met before execution
- When-to-use guidance - Clear scenarios describing when the command is applicable
- Code snippets - Optional examples demonstrating each step's implementation
Command Structure
Every command is drafted as a markdown file with this structure:
# Command Name
## Summary
What the command does, why it's useful, and when it's relevant.
## When to Use
- Scenario 1 when this command applies
- Scenario 2 when this command applies
## Context Validation Checkpoints
- Question 1 to validate before proceeding?
- Question 2 to ensure context is clear?
## Steps
### Step Name
What this step does and how to implement it.
\`\`\`typescript
// Optional code example
\`\`\`
### Another Step
Description without code.
Naming Guidelines
The # Title heading is the display name shown in indexes and dashboards. The slug is auto-generated from it — never write the slug yourself.
Format: Use Title Case with spaces — natural language, not a slug.
- Capitalize each significant word
- Start with an action verb (e.g., "Create", "Setup", "Configure")
- Use spaces between words, never hyphens or underscores
- Be descriptive and specific (2–5 words)
Examples:
- Good:
"Create API Endpoint","Setup Database Migration","Configure CI Pipeline" - Bad:
"api-endpoint"(slug format — use Title Case with spaces) - Bad:
"setup migration"(not Title Case) - Bad:
"create-api-endpoint"(slug format)
What ships with it
2 files 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.
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.
- 2d ago First seen · 351 lines · 47 tokens per session scan A 2d7ed54087de
packmind-create-command is a skill published in the GitHub repository PackmindHub/packmind (306 stars, last pushed 4d ago), licensed Apache-2.0. It adds 47 tokens to every session and 2,824 once invoked, about $0.0002 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.
Other skills, from other repositories
token-saver-config
Configure and diagnose token-saver compression settings. Use when the user asks about adjusting compression levels, checking processor status, debugging hook issues, or reviewing savings statistics.
sdd
Execute the Liatrio Spec-Driven Development (SDD) workflow when explicitly invoked by the user. NOTE: this skill is NOT intended to be dynamically loaded or automatically triggered; it should only ever be explicitly called by the user.
loadout-import-workflow
Import another repo's command/skill suite into loadout as a workflow. Use when the user points at an agent framework, plugin, or command pack (e.g. a GitHub repo, a .claude/commands/ directory, a skills pack) and wants its process turned into a loadout [[workflows]] entry — "import this workflow", "turn this plugin…
loadout-migrate
Migrate existing global AI agent instructions into loadout. Use when adopting loadout, importing a CLAUDE.md / AGENTS.md / global agent rules into loadout, setting up /.config/loadout/config.toml, or turning prose agent instructions into reusable fragments and stack-targeted profiles.
loadout-remember
Save a durable, cross-project user preference into loadout's global fragments/profiles — or update the fragment it contradicts. Use when the user states lasting guidance that should follow them across projects and agents ("always X", "never Y", "stop doing Z"), especially when it conflicts with guidance the loadout…
orchestrator
Use this skill when running as an ephemeral orchestrator subagent for a Taniwha project. The skill instructs the agent to read project state from disk, decide the single next action the dispatcher should take, write that decision back to disk, and exit. Trigger this whenever the dispatcher has invoked an orchestrator…