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/exchanet/method_enterprise_builder_planning/plan-enterprisegit clone --depth 1 https://github.com/exchanet/method_enterprise_builder_planningWrote 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.
[](https://agentmods.dev/commands/exchanet/method_enterprise_builder_planning/plan-enterprise)<a href="https://agentmods.dev/commands/exchanet/method_enterprise_builder_planning/plan-enterprise"><img src="https://agentmods.dev/badge/commands/exchanet/method_enterprise_builder_planning/plan-enterprise.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00279 |
| Opus 5 | $0.00000 | $0.00139 |
| Sonnet 5 | $0.00000 | $0.00056 |
| Haiku 4.5 | $0.00000 | $0.00028 |
Grade A, and why
plan-enterprise 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 3d 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
Command: /plan-enterprise
Starts the full 8-phase METHOD-ENTERPRISE-BUILDER-PLANNING cycle for a new enterprise system.
Usage
/plan-enterprise [description of the system to build]
What happens
- I will ask you for any missing context (system type, stack, SLA, compliance requirements)
- I will run the 8-phase cycle, asking for confirmation at each gate before proceeding
- I will produce structured documents at each phase:
- Phase 1 →
docs/enterprise-context.md - Phase 3 →
docs/risk-matrix.md - Phase 5 →
docs/adr/ADR-NNN-*.md - Phase 8 →
docs/delivery-report.md
- Phase 1 →
Example
/plan-enterprise
Payment authorization module for a retail banking platform.
Stack: Node.js + TypeScript + PostgreSQL + Kafka.
Compliance: PCI-DSS, GDPR.
SLA: 99.999%, p95 ≤ 800ms.
Notes
- You can pause at any gate and resume later with
/plan-enterprise resume phase-N - You can validate ADRs at any time with
/validate-adr docs/adr/ - You can validate micro-task sizes with
/lint-task src/module/file.ts
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.
- 3d ago First seen · 37 lines · 0 tokens per session scan A 3a56717072e4
plan-enterprise is a command published in the GitHub repository exchanet/method_enterprise_builder_planning (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 279 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 2026-08-31.
Other commands, from other repositories
graphstack
Graph-first, automatically orchestrated AI development workflow. One prompt starts the entire lifecycle — from blank repo to production.
adr
You are helping create a new ADR (Architecture Decision Record). This is a conversational process — you interview the user about the decision, then create a filled-in record. ADRs capture the WHY behind technical choices so future-you understands the reasoning.
triage-issues
Launch the Issue Triage Agent (Haiku) to categorize and prioritize GitHub issues.
adr-supersede
Create a new ADR that supersedes an existing one.
models
List models available to the local Antigravity (agy) CLI.
research
Delegate a thorough research investigation to the agy:runner subagent.