podcast

# /pika:podcast 4 acts × 15s each = 60s. Host A always LEFT, Host B always RIGHT. Accepts a URL **or** a free-form topic / brief. ## Parameters | Param | Default | Notes | |---|---|---| | `input` | required | URL to review **or** free-form topic / brief (e.g. "I and Elon Musk talk about Mars") | | `bg_img` | auto-generated | Podcast studio background | | `host_a_img` | auto-generated | Host A portrait — see Real-person handling below | | `host_b_img` | auto-generated | Host B portrait — see Real-person handling below | | `voice_a` | `876341503281471517` | Kling preset or cloned voice ID for Host A | | `voice_b` | `829837252279803904` | Kling preset or cloned voice ID for Host B | | `aspect_ratio` | `16:9` | Output aspect ratio | ## Cost transparency gate Before any paid MCP call, call `identity_balance({verbose: true})` once. Surface the current balance, recent burn rate, and remaining runway, then gate the run with this exact message: > Estimated cost: about 6,000-9,000 credits (~$60-$90) for four Kling v3-omni pro 15s acts, optional missing-asset image generation, one act corrective retry, concat, and post-flight analyze_media QA. This exceeds $5, so Reply `proceed` to continue or `cancel` to stop. Do not call any paid MCP tool until the user replies `proceed`. If the user replies `cancel`, stop without generating. This is the only yes/no gate; after `proceed`, render the four acts and return the URL. ## Defaults — fire fast, no mid-flow confirmation - **Use the param-table defaults silently for voices.** `voice_a` defaults to the Kling preset `876341503281471517` and `voice_b` to `829837252279803904`. Do **not** ask "which voice?" before firing — only honor explicit overrides (`voice_a=`, `voice_b=`). - **Auto-generate any missing host portraits silently** (Step 1's archetype prompts). Do **not** ask "should I generate a host image?" — just generate. - **Only the cost transparency gate asks for `proceed`.** After `proceed`, submit → render the 4 acts → return URL. Account credit balance + provider failover are the canonical guardrails. The `--yes` flag is accepted as a no-op for backward compatibility. - **Topic-mode personas (Step 3)** — when the user names a real public figure, follow Step 4 (Real-person handling) silently: archetype portrait by default, no auto-generated photographic likeness, no question to the user about likeness rights. ## Pre-generation wall-clock guard Start a timer at skill start once the podcast input is resolved and the cost gate has passed. The first paid generation call is `generate_image` for missing background/host assets. If all assets are already provided, the first paid generation call is `generate_reference_video`. The first paid generation call must be invoked within 5 minutes of skill start. If you have not invoked the first paid generation call within 5 minutes of skill start, stop before any paid generation call and report `failed_pre_generation_timeout` with what you have so far: input mode, asset status, voice status, URL capture/WebFetch status, script draft status, and the exact blocker. Do not keep refining host archetypes, factual grounding, jokes, or act wording. Print a single-line progress checkpoint after each prep stage and right before the paid generation call: - `Stage 1/4 done — input resolved and cost gate passed, locking missing-asset image prompts.` - `Stage 2/4 done — missing asset prompts ready, calling image generation now.` Use this right before the first paid `generate_image` call when any background or host image is missing. If all images are already provided, emit `Stage 2/4 done — assets and voices ready, collecting URL/topic facts.` instead and continue without image generation. - `Stage 3/4 done — script draft locked, preparing first act.` - `Stage 4/4 done — first act prompt ready, calling Kling now.` Missing-asset image prompt iteration is maximum 2 passes before the first `generate_image` call. After the max 2 passes, ship what you have to `generate_image`; do not continue polishing host archetypes, studio background details, or persona styling. Script and act-prompt iteration is maximum 2 passes before Kling. After the max 2 passes, ship what you have to `generate_reference_video`; do not continue polishing jokes, interruptions, persona framing, or camera wording. ## Local images on Claude Desktop Claude Desktop can't pass inline-pasted images to MCP tools yet (Anthropic-side limitation). If the user pastes a photo inline, or mentions a local file they want as `host_a_img` / `host_b_img`, pause Step 1 and kindly send them this — something like: > Heads up — pasted images don't reach MCP tools on Claude Desktop yet (Anthropic limitation). Two easy options for your photo: > > - **Paste a URL** if it's already hosted (Imgur, S3, your site) — fastest > - **Attach the image file** so I can upload it before generation. When a local file arrives, convert it to a public URL with `upload_asset` and use the returned `public_url` as the parameter before Step 1. Already-hosted `https://...` URLs work as-is and skip this entirely. If the user names a real public figure without attaching anything, do NOT auto-generate their likeness — Step 4 (Real-person handling) uses an archetype portrait instead. ## Long-running task_status polling When any long-running generation or edit call returns a `task_id` with or without an initial status, including `{task_id}`, `{task_id, status: "queued"}`, or an initial `queued`, `running`, or `processing` status, record the task id and start time immediately. - Call `task_status({task_id})` in a tight loop until terminal (`completed | failed | cancelled`). No manual sleep and no Bash polling; the worker holds each status call open. - Emit ONE visible progress line every 60s while status is `queued`, `running`, or `processing`: `Seedance i2v queued for {N}m {S}s... still processing`. Replace the provider/stage label when polling Kling, image generation, clone voice, or concat tasks. - On `completed`, unwrap the returned result URL and continue. - On `failed` or `cancelled`, surface failure to the user with `task_id`, status, and the last status message. - After 15 min total from the original submit, call `task_cancel({task_id})` if the task is still non-terminal, then surface failure to the user. If cancel reports the task is already terminal, call status once more and report that terminal result. - Do not submit a duplicate request while the original task is still `queued`, `running`, or `processing`. ## Steps ### 0. Resolve input (empty-args menu) Strip flags (`--yes`, `--no-captions`, etc.) and `key=value` parameters from `$ARGUMENTS`. **If what remains is empty or whitespace-only**, print this menu **verbatim** as your full response, then **stop and wait for the user's next message** — do NOT call any tool, do NOT proceed to Step 1, do NOT invent a topic or URL. If the stripped input is non-empty (a URL or any prose), skip this step silently and proceed to Step 1. > **What would you like a podcast about?** I can take any of: > > - **A website URL** (product page, docs site, launch page) — e.g. `https://pika.art` > - **A GitHub repo** — e.g. `https://github.com/anthropics/claude-code` > - **A blog post / article URL** — e.g. a recent piece you'd like discussed > - **A free-form topic or brief** — e.g. *"I and Elon Musk talk about Mars"* or *"two scientists debate AGI"* > > Reply with your choice and I'll generate a 1-minute two-host podcast video (4 acts × ~15s). > > *Tip: you don't need to type `/pika:podcast` — just say things like "make a podcast about <topic>", "podcast review of <url>", or "I and <persona> talk about <topic>" and I'll fire this skill automatically.* When the user replies, treat their reply as the resolved input (URL or topic) and proceed to Step 1. Do not re-prompt. ### 1. Generate missing assets (parallel) Generate only what's not provided. Default archetype prompts: - `bg_img` — modern podcast studio, two chairs, warm lighting, no people, 16:9 - `host_a_img` — enthusiastic host, studio portrait, left-side framing, 1:1 - `host_b_img` — pragmatic skeptic host, studio portrait, right-side framing, 1:1 If the input mentions specific personas (Step 3), tune the archetype to match the persona vibe — see Real-person handling below. ### 2. Resolve voice IDs Use `voice_a` / `voice_b` as given; otherwise fall back to the default Kling presets (`876341503281471517` / `829837252279803904`). If the user supplied a cloned voice ID via `voice_a=` / `voice_b=`, use it directly. ### 3. Parse input mode — URL vs topic Strip flags (`--yes`, `--no-captions`, etc.) and key=value parameters from `$ARGUMENTS`. Inspect what remains. **URL mode** — input contains a `https?://` URL: - Call `capture_website` on the URL for visual grounding only: product/page name, visible layout, screenshots, b-roll cues, and one jokeable visual detail. - Call `WebFetch` on the same URL and use its full-page text as the script source of truth. Do not rely on the screenshot alone for facts. - Extract from the combined inputs: product name, value prop, 2–3 specific features or facts, pricing, one jokeable detail, and any concrete quotes or claims. - For long-form pages (Wikipedia, docs, blog posts, or articles), scan the WebFetch full-page text for deep sections beyond the lede. When at least 3 substantive deep sections are present, the script must mention at least 3 distinct sections beyond the lede (for example architecture, training, hallucinations, limitations, deployment, or safety), not just the opening summary. - Use WebFetch text for factual anchors and `capture_website` for visuals. If they conflict, prefer WebFetch for factual claims and treat the screenshot as a visual reference. **Topic mode** — input is free-form prose (no URL): - Treat the whole input as the brief. Parse for: - **Subject** — what the conversation is about - **Hosts** — explicit if mentioned ("I and Elon Musk", "two scientists", "Joe and Sarah"); otherwise use defaults (enthusiastic host + skeptic host) - **Angle** — debate / interview / explainer / casual - **Concrete facts** — any specific claims, numbers, dates, quotes the user gave - If no concrete facts are given, use **2–3 clearly framed observations or hypotheses** to anchor jokes and the "wait, actually..." pivot. Do not present invented claims as facts; if factual accuracy matters for the topic, ask for a source or URL. - If the user says "I and X" or "me and X", Host A = the user (represented by `host_a_img=` if supplied, else a generated host portrait) and Host B = X. ### 4. Real-person handling (topic mode only) If the parsed input names a specific real public figure as a host (e.g. "Elon Musk", "Taylor Swift", "Joe Rogan"): - **Default behavior**: do NOT auto-generate that person's photographic likeness. Generate an **archetype portrait** matching the persona vibe — e.g. "tech-billionaire-energy CEO at a podcast desk" for an Elon-style host, "pop-star aesthetic" for a Taylor-style host. Clearly inspired-by, not impersonation. - **Override**: if the user explicitly provides `host_a_img=<url>` or `host_b_img=<url>`, use the provided image as-is. The user takes responsibility for likeness rights. - **Voices**: same logic — default to a generic Kling preset; only use a cloned voice when the user provides one (`voice_a=` / `voice_b=`). - **Script tone**: the dialogue can riff on the named persona's known public positions or vibe (e.g. Mars enthusiasm for Elon-style) — public-record opinions are fair game. Do NOT put specific defamatory, off-character, or fabricated-private-life statements in their mouth. This guardrail keeps the skill creative ("I want a podcast where I argue with a tech CEO about Mars") without auto-generating deepfakes of named real people. ### CJK / non-Latin handling Use this section when the URL, topic, product name, host name, quote, or required script detail includes Chinese, Japanese, Korean, Arabic, Devanagari, Cyrillic, accented Latin, emoji, or any other non-Latin text. - **Script preservation**: preserve user-supplied non-Latin characters exactly in the script state and in any factual recap. Do not romanize, transliterate, or translate product names, person names, slogans, or quoted phrases unless the user explicitly asks. If a pronunciation aid is useful, put it in nearby English prose, not as a replacement for the original characters. - **Kling voice IDs**: `voice_a=` and `voice_b=` must still be valid Kling voice IDs. For Chinese / Japanese / Korean dialogue, prefer a Kling voice ID or cloned voice sample known to speak that language; if no language-matched Kling voice is available, keep the original characters in the dialogue and surface that pronunciation may be accented instead of silently swapping to an unrelated TTS provider. - **Mixed-language dialogue**: keep each host's line short and unambiguous. Avoid asking Kling to pronounce long mixed-language paragraphs; split complex names or quotes across acts and keep surrounding English simple. - **Captions / font fallback**: this skill skips `add_captions` by default because podcast dialogue mistranscribes jargon. If the user explicitly asks for captions anyway, pass manual `subtitles[]` from the authored script rather than auto-transcribing, set `font: "noto-cjk"` for Chinese / Japanese / Korean, and preserve the original non-Latin text exactly. - **QA**: before delivery, include a one-line note in the final verdict when non-Latin text was present: whether original characters were preserved in the script and whether the selected voices were language-matched or best-effort. ### Jargon-heavy native audio handling Use this section when the URL, topic, product name, quote, or required script detail is domain-heavy or jargon-heavy, especially finance, law, medicine, AI/crypto, acronyms, coined terms, unusual product names, long numbers, or multi-word compounds. Kling-omni native TTS can garble coined terms in the spoken native audio, not just in auto-captions, so reduce the risk before the paid Kling calls. - **Risk scan**: mark the run jargon-heavy when a line would contain several domain-specific terms, acronyms, long numbers, or nested / multi-clause economist-style phrasing. Treat examples like stablecoins, unbundle, and reassure as load-bearing terms that must remain intelligible. - **Script rewrite**: preserve the canonical term in the script state and final recap, but shorten the spoken line around it. Use short lines, split long clauses, keep at most one or two high-risk terms per host line, and avoid nested clauses that make Kling infer similar-sounding filler words. - **Pronunciation aid**: create a small per-act pronunciation aid for high-risk terms, for example `stablecoins = STAY-bul coins`, `unbundle = un-BUN-dul`, `reassure = ree-uh-SHOOR`. The pronunciation aid is prompt metadata only; do not replace the canonical term in the dialogue, captions, facts, or final recap. - **Known-hard-term correction**: if a term is known to drift, or post-flight localizes a near-neighbor mishearing, do not retry the same standalone hard word. Keep the canonical term in act metadata (`canonical_terms: ["unbundle"]`), then make the corrected voice-token line a short context phrase with a speakable cue / micro-pause, for example `we un-bundle payments`. Add the observed wrong form as a negative pronunciation guard in metadata, for example `unbundle = un-BUN-dul, not un-bumble`. - **Known-hard publishable fallback**: before the paid Kling calls, mark observed hard terms such as `unbundle` as known-hard when prior E2E or the current post-flight findings show drift like `unbundle` -> `unbubble`, `un-bumble`, or `unbundable`. Record `canonical_terms` and `observed_wrong_forms`. Do not render known-hard spoken terms with Kling native audio. Instead, generate the affected visual act or final video with no spoken known-hard term in the native voice-token lines, then generate controlled narration with `generate_speech(text=<spoken-only script>, provider: "minimax-tts", minimax_model: "speech-2.8-hd", language: "en")` using the canonical spelling (`unbundle`, not the hyphen cue). The spoken-only script must preserve the authored host-turn order but contain no HOST_A/HOST_B labels, no metadata, no pronunciation aids, and no observed wrong-form spellings. Run pre-replacement QA on the TTS audio with both `transcribe_audio(audio=<tts_audio_url>)` and `analyze_media(media=<tts_audio_url>)`; every required `canonical_terms` entry must appear in the `transcribe_audio` text and must appear in the `analyze_media` observed transcript. Reject the TTS if a canonical term is missing, replaced by any observed wrong form, or replaced by a new near-neighbor. Then call `edit_audio_replace(video_url=<final_mp4>, audio_url=<tts_audio_url>, duration_policy: "video")` to discard the native audio and replace it with the controlled TTS track. Run post-replacement QA on the replaced MP4 with both `transcribe_audio(audio=<replaced_mp4_url>)` and `analyze_media(media=<replaced_mp4_url>)`; every required `canonical_terms` entry must appear in both final checks, and `analyze_media` must also verify host-turn order and acceptable audio/video sync. If any final check hears a wrong form, misses a canonical term, or says the fallback collapses the podcast turn structure, return `not publish-ready`; if both checks pass, the fallback output is publish-ready even though it uses controlled TTS instead of Kling native speech. - **Numbers and acronyms**: write spoken-friendly forms when they matter: `$175B` becomes `one hundred seventy-five billion dollars`; `API` becomes `A P I` unless the brand normally says it as a word. - **Act prompt**: include the per-act pronunciation aid near the voice-token lines with an instruction that it is not dialogue and should not be spoken verbatim. Ask for clear pronunciation of the canonical terms and no improvising similar words. ### 5. Write script Write 4 acts × 2 lines (HOST_A / HOST_B). Each line ~10–12s of spoken dialogue. **Required (apply to both URL and topic modes):** - One specific joke tied to a concrete detail (scraped fact in URL mode; topic-derived claim in topic mode) - One "wait, actually..." skeptic-flip moment - At least one mid-sentence interruption - Natural filler: "okay so", "wait", "right?", "i mean", "honestly" - Real reactions, not generic praise - Reference at least one actual feature name, price, claim, or quote - Natural ending — no forced "bye!" - Apply Jargon-heavy native audio handling before finalizing the act lines when the topic is domain-heavy, jargon-heavy, or uses coined terms. Acts: Hook → Feature deep-dive → The Turn → Verdict (In topic mode the analogue: Hook → Substance → The Pivot → Verdict.) ### 6. Generate video acts (subagent, sequential) Delegate to a subagent with all resolved assets and the script. The subagent runs acts 1→2→3→4 sequentially — do NOT parallelize. The subagent must follow the Long-running task_status polling contract above and relay every 60s progress line back to the parent while it is waiting on Kling, image generation, voice clone, or concat tasks. Each normal act: one `generate_reference_video` call (`kling-v3-omni`, `duration=15`, `sound=true`, `quality_mode: "pro"`). Pass `reference_images=[bg_img, host_a_img, host_b_img]`, `voice_ids=[voice_a, voice_b]`, and `quality_mode: "pro"` on every normal act; this must pass `quality_mode: "pro"` because the cost gate quotes the pro-tier 15s act cost. Optional knob: `kling_model` to pin a specific kling family member if you need reproducibility across runs. Three shots: - **Known-hard fallback exception**: for acts containing known-hard spoken terms, render the affected visual act with `sound=false` and no voice tokens for the affected lines. Do not include canonical known-hard terms in any `<<<voice_*>>>` native voice-token line; the controlled TTS replacement supplies those words later. For jargon-heavy but not known-hard acts, include the per-act pronunciation aid from Step 5 in the act prompt as non-dialogue metadata and preserve canonical terms in the quoted `<<<voice_*>>>` lines. - Wide 5s: both hosts, no voice token - MCU-A 5s: `<<<voice_1>>> '<HOST_A line>'` - MCU-B 5s: `<<<voice_2>>> '<HOST_B line>'` Emotional beats per act: - Act 1: A excited, B skeptical - Act 2: A gesturing/explaining, B questioning - Act 3: A firm, B surprised and reconsidering - Act 4: A satisfied, B conceding After act 4, subagent calls `edit_concat([act1, act2, act3, act4])`, relays any async polling progress to the parent, and returns the final video URL. Keep the four act URLs in state so the post-flight quality gate can spend at most one targeted act correction without regenerating clean acts.