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 commands/talayash/agentrium/plangit clone --depth 1 https://github.com/talayash/agentriumWhat 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 | $0.00000 | $0.00293 |
| Opus 5 | $0.00000 | $0.00147 |
| Sonnet 5 | $0.00000 | $0.00059 |
| Haiku 4.5 | $0.00000 | $0.00029 |
Grade A, and why
plan 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.
What it actually says
Plan
Create a detailed implementation plan before writing any code.
Instructions
You are about to plan the implementation of: $ARGUMENTS
Follow this process strictly:
Step 1: Restate Requirements
- Restate what the user wants in your own words
- List specific acceptance criteria
- Identify any ambiguities - ask if unclear
Step 2: Assess Current State
- Read relevant files in
src/(frontend) andsrc-tauri/src/(backend) - Identify ALL files that will need changes
- Note existing patterns to follow
Step 3: Risk Assessment
Evaluate:
- Breaking changes to IPC contracts?
- New Zustand store fields needed?
- PTY/terminal lifecycle impact?
- Database schema changes?
- Windows-specific concerns?
Step 4: Create Phased Plan
For each phase:
- Files to modify/create (exact paths)
- What changes in each file
- Dependencies between phases
- How to verify the phase works
Step 5: Present Plan
Format as:
# Plan: [Feature Name]
## Requirements: ...
## Risk Assessment: ...
## Phase 1: [Name] - Files, Changes, Test
## Phase 2: [Name] - Files, Changes, Test
## Complexity: S/M/L/XL
WAIT for user confirmation before implementing. Ask: "Does this plan look good?"
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 · 48 lines · 0 tokens per session scan A 38f354cf2be8
plan is a command published in the GitHub repository talayash/agentrium (39 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 293 tokens. 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 commands, from other repositories
spec-design
Create comprehensive technical design for a specification.
vibe-agents
Step 4 of the vibe-coding workflow: generate AGENTS.md + tool configs so the AI builder stays on track.
goal
Register a completion condition and arm the autonomous continuation loop.
loop
Iteratively fix issues until all resolved or max iterations reached.
project
Generate project documentation (product.md, structure.md, tech.md, codemaps/).
review
Code review with security and @MX tag compliance check.