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/phases)<a href="https://agentmods.dev/commands/jonase47/ccpr/phases"><img src="https://agentmods.dev/badge/commands/jonase47/ccpr/phases/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/phases"><img src="https://agentmods.dev/badge/commands/jonase47/ccpr/phases.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 | $0.04223 |
| Opus 5.5 | $0.00000 | $0.01689 |
| Sonnet 5.5 | $0.00000 | $0.00845 |
| Haiku 4.5 | $0.00000 | $0.00422 |
Grade A, and why
phases 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.
How it starts
The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phase Commands (82 commands, P0–P8)
All P0–P8 phase commands grouped per phase. Lead commands appear first, then sub-commands in execution sequence where applicable.
P0: Discovery (3 commands)
| Command | Title | Description |
|---|---|---|
/p0-problem |
Problem Definition & Target Audience Identification | Defines the core problem of a project or business idea and identifies the first rough Target Audience. The result is a clear problem statement that serves as the foundation for all subsequent phases. |
/p0-market |
Market Assessment & Competition Overview | Delivers a first market assessment: Is there demand? Who are the competitors? Is the idea roughly viable economically? The result is an overview needed for the Go/No-Go Decision at Gate 0. |
/p0-regulatory |
Regulatory & Legal Knock-Out Criteria | Identifies regulatory requirements, DSGVO (GDPR) obligations, and legal knock-out criteria early on, before significant time is invested in the idea. A regulatory showstopper should be recognised as early as possible. |
P1: Conception (5 commands)
| Command | Title | Description |
|---|---|---|
/p1-journeys |
Personas & User Journeys | Develops detailed personas, user journeys, and usage scenarios based on the Discovery results. These artefacts form the user foundation for all further conception decisions. |
/p1-features |
Feature Definition & MVP Scope Boundary | Defines the feature scope of the project, prioritises using MoSCoW, and clearly defines the MVP scope. The result is FEATURES.md and MVP.md as the binding basis for architecture and planning. |
/p1-business-model |
Business Model Canvas & Value Proposition | Develops the Business Model with Business Model Canvas, sharpens the value proposition, and defines a first pricing approach. The result is BUSINESS_MODEL.md as the economic foundation of the project. |
/p1-financial-plan |
Cost Structure, Revenue Forecast & Break-Even | Creates a first financial plan with Cost Structure, Revenue Forecast, and break-even analysis. The goal is not exact bookkeeping but a plausible set of numbers that demonstrates the economic viability of the venture. |
/p1-privacy |
Data Classification & DSGVO Initial Assessment | Conducts a systematic initial assessment of data protection requirements: What personal data is processed, on what legal basis, and what DSGVO (GDPR) obligations arise from this? The result is a well-founded DSGVO initial assessment as a mandatory component of the Concept. |
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 Changed c131ce6fae15
- 1mo ago First seen · 146 lines · 0 tokens per session scan A 2f605a8d57bb
phases is a command published in the GitHub repository jonase47/ccpr (1 stars, last pushed 26d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,223 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.