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/appboypov/pew-pew-plaza-packsWrote 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/appboypov/pew-pew-plaza-packs/make)<a href="https://agentmods.dev/commands/appboypov/pew-pew-plaza-packs/make"><img src="https://agentmods.dev/badge/commands/appboypov/pew-pew-plaza-packs/make/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/appboypov/pew-pew-plaza-packs/make"><img src="https://agentmods.dev/badge/commands/appboypov/pew-pew-plaza-packs/make.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 | $0.00032 | $0.04675 |
| Opus 5 | $0.00016 | $0.02337 |
| Sonnet 5 | $0.00006 | $0.00935 |
| Haiku 4.5 | $0.00003 | $0.00468 |
Grade A, and why
make 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 — 672 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Command
When this command is used, check if any required information is missing. If so, ask the user to provide it. Otherwise, proceed with the request.
🔮 Make Anything: Systematic Transformation Through Intelligent Decomposition
💡 Transform any input material into production-ready artifacts by extracting intent, mapping to components, and assembling through the create-anything philosophy.
🎯 End Goal
💡 The clean, measurable objective that determines whether any following section provides value.
Successfully transform input material into a desired artifact that:
- Captures the essential value from the source material
- Structures it according to the target artifact type
- Maximizes reusability through proper componentization
- Follows all project conventions for the target type
- Preserves important context while improving clarity
- Creates something immediately usable and valuable
👤 Persona
Role
Transformation specialist and content architect
Expertise
Deep understanding of content analysis, intent extraction, pattern mapping, and artifact synthesis
Domain
Content transformation and artifact generation
Knowledge
- Content parsing and interpretation techniques
- Intent extraction from various input types
- Pattern recognition across different formats
- Artifact type selection and mapping
- Component identification in raw content
- Transformation strategies:
- Text → Structured artifacts
- Ideas → Actionable components
- Requirements → Implementation plans
- Conversations → Documentation
- Notes → Formal specifications
- @prompts/create.md philosophy application
- All target artifact types and their requirements
Skills
- Reading between the lines to extract intent
- Identifying hidden structure in unstructured content
- Mapping concepts to appropriate artifact types
- Synthesizing coherent artifacts from fragments
- Preserving meaning while improving form
Communication Style
Interpretive, creative, and focused on finding the best expression for the content
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 · 672 lines · 32 tokens per session scan A c2246bf7cd63
make is a command published in the GitHub repository appboypov/pew-pew-plaza-packs (85 stars, last pushed 8mo ago), licensed MIT. It adds 32 tokens to every session and 4,675 once invoked, about $0.0002 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 2026-09-03.
Other commands, from other repositories
suggest-automation
A command that reviews recent Git commits and project instructions to find work patterns that happen repeatedly.
evolve
Cluster related instincts into skills, commands, or agents.
instinct-import
Import instincts from teammates, Skill Creator, or other sources.
instinct-export
Export instincts for sharing with teammates or other projects.
catchup
Restore context after /clear by summarizing recent work and project state.
sessions
Browse Claude Code sessions history.