Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add pwdev-solucoes/pwdev-claude-marketplace/plugin install pwdev-social-mediaWrote 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/pwdev-solucoes/pwdev-claude-marketplace/carrossel)<a href="https://agentmods.dev/commands/pwdev-solucoes/pwdev-claude-marketplace/carrossel"><img src="https://agentmods.dev/badge/commands/pwdev-solucoes/pwdev-claude-marketplace/carrossel/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/pwdev-solucoes/pwdev-claude-marketplace/carrossel"><img src="https://agentmods.dev/badge/commands/pwdev-solucoes/pwdev-claude-marketplace/carrossel.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 | $0.00021 | $0.00265 |
| Opus 5 | $0.00010 | $0.00133 |
| Sonnet 5 | $0.00004 | $0.00053 |
| Haiku 4.5 | $0.00002 | $0.00026 |
Grade A, and why
carrossel 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.
What it actually says
/pwdev-social-media:carrossel
STEP 0 — Idioma
${CLAUDE_PLUGIN_ROOT}/references/language.md
STEP 1 — Insumos
Copy slide a slide (sem ela → /pwdev-copy:copy social), plataforma, contagem.
| Plataforma | Ideal |
|---|---|
| 8-10 slides, 1080 × 1350 | |
| 7-12 slides, PDF 1080 × 1350 | |
| 5-8 slides |
Abaixo de 5 slides: proponha post único.
STEP 2 — Conceito e montagem
art-director → aprovação → figma-builder seguindo carousel-builder.
Slide é componente com variantes, nunca frames soltos.
STEP 3 — Revisar
creative-reviewer. Carrossel exige alt text por slide — é o formato que
mais falha em acessibilidade.
STEP 4 — Exportar
export-handoff. LinkedIn: PDF.
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 · 33 lines · 21 tokens per session scan A d24d0eea7033
carrossel is a command published in the GitHub repository pwdev-solucoes/pwdev-claude-marketplace (2 stars, last pushed 4d ago), licensed Apache-2.0. It adds 21 tokens to every session and 265 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 2026-09-03.
Other commands, from other repositories
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Command "rive-interactive-viewmodel_builder" from freshtechbro/claudedesignskills, covering /rive-interactive-viewmodelbuilder, description, usage, implementation and notes.
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Create a design based on video.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.