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.
npx skills add THU-SAGE/syll --skill morning-podcastgit clone --depth 1 https://github.com/THU-SAGE/syllWrote 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/thu-sage/syll/morning-podcast)<a href="https://agentmods.dev/skills/thu-sage/syll/morning-podcast"><img src="https://agentmods.dev/badge/skills/thu-sage/syll/morning-podcast/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/thu-sage/syll/morning-podcast"><img src="https://agentmods.dev/badge/skills/thu-sage/syll/morning-podcast.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 | $0.00017 | $0.00586 |
| Opus 5.5 | $0.00007 | $0.00234 |
| Sonnet 5.5 | $0.00003 | $0.00117 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
morning-podcast 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 2mo 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
Morning Podcast
Triggered either by the user saying "morning podcast" / "晨间播客" or
by a cron job that runs this skill on a schedule. The output is a
single audio file (via the speak tool) that the web frontend will
auto-render as an <audio> element; if the job is delivering to a
messaging channel, the MP3 travels along the outbound message.
Steps
-
Collect stories. Use
web_searchto gather 3–5 items across tech, world, and markets. One or two searches is usually enough:web_search(query="今日科技头条", count=5) web_search(query="today world news", count=5)Skim titles/snippets, pick the most substantive stories, and drop anything paywalled or clickbait-y.
-
Summarize in spoken form. For each story, write ~80–120 Chinese characters (or ~40 English words). No markdown. No URLs in the spoken body — reference the outlet by name instead. Rewrite headlines into natural narration ("今天…", "另一边…").
-
Compose one script. Assemble a single continuous string:
- Greeting using
{{ghost_name}}, e.g. "{{ghost_name}} 早安播 报,今天是 X 月 Y 日。" - Item 1 → item N with short transitions.
- Sign-off: "以上就是今天的晨间播报,{{user_name}},祝你有个顺 利的一天。"
- Greeting using
-
Call
speakexactly once with the full script:speak(text="<full assembled script>")A single call yields the best prosody. Do not call
speakper-item — concatenating multiple clips sounds choppy. -
Reply briefly. One sentence summarizing what's in the briefing (e.g. "今日播报已生成:科技 / 市场 / 国际 共 4 条"). The audio itself is attached through the tool result's
media— you don't need to repeat the script in the reply.
Notes
- Real tool name is
web_search(notweb.search) andspeak. - If
speakfails, fall back to a text-only briefing and tell the user why ("TTS unavailable: …"). - Never include URLs in the TTS input — Volcengine reads them out character-by-character and it sounds terrible.
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.
- 2mo ago First seen · 57 lines · 17 tokens per session scan A e295e4e6fdd7
morning-podcast is a skill published in the GitHub repository THU-SAGE/syll (304 stars, last pushed 5mo ago), licensed MIT. It adds 17 tokens to every session and 586 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.
morning-podcast compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| morning-podcastTHU-SAGE/syll | Skill | 304 | 5mo ago | MIT | A | 17 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |