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/provider-research-digest/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/provider-research-digest)<a href="https://agentmods.dev/skills/pipecat-ai/pipecat/provider-research-digest"><img src="https://agentmods.dev/badge/skills/pipecat-ai/pipecat/provider-research-digest/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/provider-research-digest"><img src="https://agentmods.dev/badge/skills/pipecat-ai/pipecat/provider-research-digest.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 | $0.00042 | $0.00776 |
| Opus 5 | $0.00021 | $0.00388 |
| Sonnet 5 | $0.00008 | $0.00155 |
| Haiku 4.5 | $0.00004 | $0.00078 |
Grade A, and why
provider-research-digest 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Render digests/<date>.md in the reports checkout from every report carrying the date, topped with highlight bullets you author. The digest is a function of the reports on disk, not of any one research run — re-running this skill after further same-date research replaces the digest with a fresh view of the whole date. Everything stays local — this skill publishes nothing; pushing the digest and opening the digest issue are scripts/provider-watch/publish.py --finalize's job, run afterwards by whoever invoked this.
Arguments
/provider-research-digest [--date YYYY-MM-DD]
--date YYYY-MM-DD— the date to digest. Defaults to today.
Instructions
Step 1: Sync the reports checkout
Record RUN_DATE as --date if given, else today's date (YYYY-MM-DD), and pick a scratch directory outside the repo (your session scratchpad if you have one, else mktemp -d -t provider-research-digest). The reports checkout is always ./_reports in this repo (gitignored). If it is missing, gh repo clone pipecat-ai/provider-watch-reports _reports; if it exists and has a remote, git -C _reports pull --ff-only — the digest must see every report published for the date, not a stale checkout. Stop with a clear error if no _reports/reports/*/*/<RUN_DATE>.md exists.
Step 2: Render a draft
uv run python scripts/provider-watch/digest.py --reports _reports --date <RUN_DATE> --out <scratch>/digest-draft.md
Read the draft: it aggregates every unit's summary, PRs, changes to consider and errors for the date.
Step 3: Author the highlights
Write up to 5 highlight bullets to <scratch>/highlights.md from the draft: what a maintainer should look at first — services broken out of the box, PRs and branches worth reviewing first, long-open gaps that finally moved, providers that errored. Judge from the whole date, not from whichever units were researched most recently, and skip bullets when nothing stands out. Match the draft's conventions (unit ids and code in backticks, report paths where a pointer helps).
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 · 49 lines · 42 tokens per session scan A 9c9aa1d15772
provider-research-digest is a skill published in the GitHub repository pipecat-ai/pipecat (15,323 stars, last pushed yesterday), licensed BSD-2-Clause. It adds 42 tokens to every session and 776 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 2026-09-02.
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