Borrowing it
Nothing to install: this file belongs to Kandil7/prprompts-flutter-generator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Kandil7/prprompts-flutter-generator/master/.claude/commands/prprompts/phase-3.mdgit clone --depth 1 https://github.com/Kandil7/prprompts-flutter-generatorWrote 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/kandil7/prprompts-flutter-generator/phase-3)<a href="https://agentmods.dev/commands/kandil7/prprompts-flutter-generator/phase-3"><img src="https://agentmods.dev/badge/commands/kandil7/prprompts-flutter-generator/phase-3.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 | $0.00025 | $0.01970 |
| Opus 5 | $0.00013 | $0.00985 |
| Sonnet 5 | $0.00005 | $0.00394 |
| Haiku 4.5 | $0.00003 | $0.00197 |
Grade A, and why
Generate Phase 3 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 7d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Phase 3: Demo & Learning (v2.0)
Overview
Generate the 10 demo and learning PRPROMPTS files plus README, following v2.0 strict PRP pattern.
Input
Read: docs/PRD.md - Extract YAML frontmatter for customization.
V2.0 SPECIFICATION
PRP Pattern (MANDATORY)
Every file MUST follow this exact 6-section structure:
## FEATURE
What this guide helps you accomplish
## EXAMPLES
Real code with actual file paths
## CONSTRAINTS
✅ DO / ❌ DON'T rules
## VALIDATION GATES
Manual checklist + automated CI checks
## BEST PRACTICES
Junior-friendly "Why?" explanations
## REFERENCES
Official docs, tools, templates
Quality Requirements
- ✅ Length: 500-600 words per file (README: 300-400 words)
- ✅ No Placeholders: All content actionable
- ✅ Real Examples: Actual code, workflows, templates
- ✅ Junior-Friendly: Explain benefits and rationale
- ✅ PRD-Adapted: Files 26 and 31 heavily customized
Output
IMPORTANT: All files MUST go inside the PRPROMPTS/ folder.
Files to Generate (10 files + README, numbered 23-32)
-
23-ai_pair_programming_guide.md (500-600 words)
- Claude Code, GitHub Copilot integration
- AI-assisted refactoring, test generation
- Human review required for AI code
-
24-dashboard_and_analytics.md (500-600 words)
- Firebase Analytics, Crashlytics
- Event tracking, performance monitoring
- Privacy review, NO logging PII/PHI
-
25-tech_debt_and_refactor_strategy.md (500-600 words)
- Debt scoring (High/Medium/Low)
- 20% sprint capacity for refactors
- GitHub Issues labeled
tech-debt
-
26-demo_environment_setup.md (500-600 words) ⭐ PRD-CUSTOMIZED
- MUST adapt based on PRD's
project_type - Healthcare: Pre-populated patient records
final demoPatientsHealthcare = [ Patient(id: '1', name: 'John Doe', condition: 'Diabetes'), ]; - Fintech: Test credit cards (4242...)
final demoCardsFintech = [ CreditCard(last4: '4242', brand: 'Visa', expiryMonth: 12, expiryYear: 2025), ]; - Education: Sample courses and students
- E-commerce: Demo products, orders
- SaaS: Sample workspaces, users
- MUST adapt based on PRD's
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.
- 7d ago First seen · 224 lines · 25 tokens per session scan A 91d02d36a507
Generate Phase 3 is a command published in the GitHub repository Kandil7/prprompts-flutter-generator (11 stars, last pushed 9mo ago), licensed MIT. It adds 25 tokens to every session and 1,970 once invoked, about $0.0001 per session on Opus 5. 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
speckit.gym.drop
Record a drop card from a mis-fire. A mis-fire is not a mistake to punish — it is a discovery to keep. Drop cards capture what was done, what was expected, and what happened, persisted to the configured redundant stores (default /drops/ plus the extension's append-only .drop-ledger.md).
speckit.gym.run
Full training run: warmup reps grow reflexes, graded exercises prove skill under load, and the gate opens only when every rep is grown and every exercise is passed.
speckit.gym.gate
Query the current gate state. This is the host-enforcement surface: a host (CLI, CI, service, or the optional beforeimplement hook) queries it before letting an operator perform the real task.
speckit.gym.init
Scaffold a starter GYM curriculum in the current Spec Kit project so its operators can be trained and gated.
speckit.gym.warmup
Warmup only — grow the operator's reflexes without the graded exercises. Skips Phase 2 entirely.
progress
Show detailed progress report for current learning topic.