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/jonase47/ccpr/p7-preparegit clone --depth 1 https://github.com/jonase47/ccprWrote 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/jonase47/ccpr/p7-prepare)<a href="https://agentmods.dev/commands/jonase47/ccpr/p7-prepare"><img src="https://agentmods.dev/badge/commands/jonase47/ccpr/p7-prepare.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 5.1 | $0.00000 | $0.01365 |
| Opus 5 | $0.00000 | $0.00682 |
| Sonnet 5 | $0.00000 | $0.00273 |
| Haiku 4.5 | $0.00000 | $0.00136 |
Grade A, and why
p7-prepare 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/p7-prepare – Deployment Preparation & Pre-Launch Checklist
Prepares the deployment: checks all environments, prepares database migrations, verifies configurations, and ensures nothing has been overlooked. Only after this checklist is complete will /p7-deploy be executed.
Argument: $ARGUMENTS = [Environment, e.g. "staging", "production"]
If provided: Prepare the deployment for the specified environment. If not provided: Ask for the target environment. Default order is staging first, then production – confirm or adjust accordingly.
Execution
1. Read Context
Read the following files (if available):
- INFRASTRUCTURE.md (Hosting, Environments, Rollback strategy)
- GATE_P6.md (Approval status – deployment only after Gate 6 has passed)
- SECURITY.md (Security requirements for production deployment)
- DSGVO_INITIAL_ASSESSMENT.md (DSGVO (GDPR) obligations before go-live)
- DATA_MODEL.md (Identify database migrations)
2. Verify Gate 6 Approval
Before preparation starts: Does GATE_P6.md exist with a green or yellow approval from both reviewers? If not: Stop and point out that Gate 6 must be completed first.
3. Delegation to DevOps Agent (Lead)
Delegate deployment preparation to the devops agent:
Prepare the deployment for the following environment: $ARGUMENTS Context from INFRASTRUCTURE.md: [Apply hosting, environment configurations, CI/CD pipeline]
A. Environment Check
- Are all required environment variables set in the target environment?
- Are configurations correct (CORS origins, Allowed Hosts, API URLs) for the target environment?
- Are all external services (email, payment, monitoring) configured for the target environment?
- Are secrets correctly stored (database passwords, API keys, certificates)?
B. Database Migrations
- Which migrations need to be executed for this deployment?
- Have all migrations been successfully tested on the staging environment?
- Are there destructive migrations (DROP COLUMN, DELETE)? If so: backup beforehand?
- Is a rollback of the migrations possible if needed?
C. Deployment Artifacts
- Is the release branch clearly identified and tagged (e.g. v1.0.0)?
- Are all CI checks passing on the release tag?
- Are Docker images built and available in the container registry?
D. Rollback Plan
- What is the rollback procedure if the deployment fails?
- How long does a rollback take?
- Who is responsible for the rollback decision?
- Are the database state and application code consistent during a rollback?
E. Downtime Planning
- Is a maintenance page/maintenance mode prepared for the deployment?
- Is there a zero-downtime deployment (Blue/Green, Rolling Update)?
- If downtime is unavoidable: what is the best time window?
F. Pre-Launch Checklist Create a concrete, actionable checklist for the upcoming deployment. Each item should be checkable as ✅/❌.
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 · 120 lines · 0 tokens per session scan A 86ee1faeaddb
p7-prepare is a command published in the GitHub repository jonase47/ccpr (1 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,365 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 2026-09-03.
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