Pipecat is an open-source Python framework for building real-time conversational agents that work with voice, video, images, and other media. It is for creating voice assistants, companions, business agents, and multi-agent systems from modular conversation pipelines.
Borrowing it
Nothing to install: this file belongs to pipecat-ai/pipecat. 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/pipecat-ai/pipecat/main/.claude/skills/pr-submit/SKILL.mdgit clone --depth 1 https://github.com/pipecat-ai/pipecatWrote 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/skills/pipecat-ai/pipecat/pr-submit)<a href="https://agentmods.dev/skills/pipecat-ai/pipecat/pr-submit"><img src="https://agentmods.dev/badge/skills/pipecat-ai/pipecat/pr-submit/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/skills/pipecat-ai/pipecat/pr-submit"><img src="https://agentmods.dev/badge/skills/pipecat-ai/pipecat/pr-submit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00014 | $0.00335 |
| Opus 5.5 | $0.00006 | $0.00134 |
| Sonnet 5.5 | $0.00003 | $0.00067 |
| Haiku 4.5 | $0.00001 | $0.00034 |
Grade A, and why
pr-submit 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
Submit the current changes as a GitHub pull request.
Instructions
-
Check the current state of the repository:
- Run
git statusto see staged, unstaged, and untracked changes - Run
git diffto see current changes - Run
git log --oneline -10to see recent commits
- Run
-
If there are uncommitted changes relevant to the PR:
- Ask the user if they want a specific prefix for the branch name (e.g.,
alice/,fix/,feat/) - Create a new branch based on the current branch
- Commit the changes using multiple commits if the changes are unrelated
- Ask the user if they want a specific prefix for the branch name (e.g.,
-
Run
/prose-review branchand fix anything it flags. Do this before pushing, while corrections are still cheap. -
Push the branch and create the PR:
- Push with
-uflag to set upstream tracking - Create the PR using
gh pr create
- Push with
-
After the PR is created:
- Run
/changelog <pr_number>to generate changelog files, then commit and push them - Run
/pr-description <pr_number>to update the PR description
Both skills review their own prose — no separate pass is needed here.
- Run
-
Return the PR URL to the user.
Commit messages are prose too — /prose-review reads diffs and so won't see them.
Read the messages in git log main..HEAD against the same standard before pushing.
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 · 37 lines · 14 tokens per session scan A 5eb237dbfb01
pr-submit is a skill published in the GitHub repository pipecat-ai/pipecat (16,618 stars, last pushed today), licensed BSD-2-Clause. It adds 14 tokens to every session and 335 once invoked, about $0.0001 per session on Opus 5.5. 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 skills, from other repositories
understand-pr
Review a PR the way a seasoned maintainer would — build an independent model before seeing the diff, investigate the implementation and history, verify material claims, and return a concise briefing. Use for any PR review, self-review, or re-review.
herdr-kit-workflows
Set up and operate Herdr Kit safely: install and configure the plugin and Mastra Code integration, manage Review and Work repository scope, open primary repository workspaces, synchronize managers, materialize or dematerialize managed worktrees, and update Herdr Kit settings or shortcuts.
factory-gitlab-review
Review a GitLab merge request for a Factory work item using brokered source-control tools.
factory-gitlab-rereview
Re-review a GitLab merge request after new commits and reconcile the previous review.
triage-issue
First-contact triage for a GitHub issue.
herdr-manager-query
Query the authoritative global Herdr Review and Work Manager inventory, recommend actionable PR work, and explicitly materialize confirmed remote-only Review Manager records through the plugin's stable public CLI.