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.
git 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/gates)<a href="https://agentmods.dev/commands/jonase47/ccpr/gates"><img src="https://agentmods.dev/badge/commands/jonase47/ccpr/gates/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.
<a href="https://agentmods.dev/commands/jonase47/ccpr/gates"><img src="https://agentmods.dev/badge/commands/jonase47/ccpr/gates.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00647 |
| Opus 5.5 | $0.00000 | $0.00259 |
| Sonnet 5.5 | $0.00000 | $0.00129 |
| Haiku 4.5 | $0.00000 | $0.00065 |
Grade A, and why
gates 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 1mo 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
Gates (12 commands)
Quality gates between phases — single-purpose decision points. Main gates (P0–P7) plus sub-gates for the dual-approval gates P6 (QA + Security) and P7 (Tech + Business).
| Command | Title | Description |
|---|---|---|
/gate-p0 |
Quality Gate 0: Discovery → Conception | Checks whether all criteria of the Discovery phase have been met and prepares the Go/No-Go Decision. No argument – this gate always checks the complete checklist. |
/gate-p1 |
Quality Gate 1: Conception → Validation | Checks whether all results of the conception phase are complete and robust, and prepares the transition to the validation phase. No argument – this gate always checks the complete checklist. |
/gate-p2 |
Quality Gate 2: Validation → Architecture | Checks whether all critical Assumptions have been validated and a well-founded Go/No-Go/Pivot Decision can be made. This is the most important gate in the model – here it is decided whether to invest in the cost- and time-intensive architecture and implementation phase. No argument – this gate always checks the complete checklist. |
/gate-p3 |
Quality Gate 3: Architecture & Design → Planning | Checks whether all architecture and design decisions are completely documented and robust before transitioning into the planning and implementation phase. No argument – this gate always checks the complete checklist. |
/gate-p4 |
Quality Gate 4: Planning → Implementation | Checks whether all organizational and technical prerequisites are met to begin implementation. This is a readiness gate – all participants must know what to do first. No argument – this gate always checks the complete checklist. |
/gate-p5 |
Sprint Gate: Check Implementation Quality | Checks at the end of each sprint whether all tasks meet quality standards and the sprint can be considered successfully completed. Called repeatedly after each sprint. No argument – this gate always checks the complete current sprint status. |
/gate-p6-qa |
QA Approval Evaluation | Evaluates all QA-relevant points of the Gate-P6 checklist and grants QA approval. |
/gate-p6-security |
Security Approval Evaluation | Evaluates all security-relevant points of the Gate-P6 checklist and grants Security approval. |
/gate-p6 |
Release Gate: QA & Security Approval | Checks whether the system is ready for launch. Both QA and Security must explicitly grant approval. No go-live without dual approval. |
/gate-p7-tech |
Technical Go-Live Check | Checks technical go-live readiness: deployment, monitoring, rollback, smoke tests. |
/gate-p7-business |
Business Readiness Check | Checks business readiness: documentation, GTM, KPIs, legal mandatory documents. |
/gate-p7 |
Go-Live Gate: Technical Readiness & Business Readiness | Checks whether the system is fully ready for production operation. Last gate before the official go-live status. |
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.
- 1mo ago First seen · 26 lines · 0 tokens per session scan A b16fbf109f74
gates is a command published in the GitHub repository jonase47/ccpr (1 stars, last pushed 24d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 647 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
stats
Show real token usage, delegation rate, and actual savings for the current Hydra session (parses Claude Code session JSONL — no AI estimation).
map
View, rebuild, or query the codebase dependency map.
design-intent
Guided UI/visual development with structured exploration, architecture design, and quality review.
ralph
Ralph autonomous development loop with fresh context per iteration.
debug
Systematic debugging with automated investigation and 4-phase methodology. Default: inline evidence gathering and diagnosis. --deep: spawns systematic-debugger agent for full autonomous debugging. Use for errors, stack traces, test failures, or unexpected behavior.
double-check
Comprehensive verification with automated quality gates, confession gathering, and confidence-based issue filtering. Default: self-review with gates. --deep: multi-agent review via code-reviewer agent. Use before committing, after fixing bugs, or to validate feature completeness.