Clip Editorial — Story-First Podcast Clipping
Find meaningful podcast stories with complete payoffs, context checks, and source ranges.
$9
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Claude Code
Cursor
Codex CLI
Muse
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Grok Bot+18 agentsClip Editorial — Story-First Podcast Clipping
Example session with this skill installed
Use Clip Editorial on the included fictional transcript for an audience of new managers. Recommend complete stories with a useful spoken payoff, explain what to reject, and propose source boundaries. Stop before production. Treat the synthetic timestamps as test data, not verified audio.
- Read your context and instructions
- Compiled the clip editorial
Recommendation: the changing-priorities story
This demonstration uses the included fictional transcript with synthetic timestamps. It illustrates the editorial output; it is not a customer result or an audiovisual review.
Only one candidate passes. The fixture contains two possible moments, so a five-item shortlist would invent material.
| Candidate | Source speech | Decision | Viewer value |
|---|---|---|---|
| Changing priorities | 00:30–00:57 | Recommend for rough-cut review | A new manager can recognize how their own changing priorities contribute to the delays they blame on others. |
| Working late | 00:00–00:10 | Hold; no payoff in supplied context | A familiar difficulty is named, but no consequence or change is delivered. |
The recommended story
- Setup, 00:30: “I blamed my team for missing deadlines.”
- Turn, 00:40: “Then I checked my messages. I had changed the priority every day.”
- Payoff, 00:50: “I stopped changing it. We finally finished the project.”
Fidelity passes for the supplied text. Significance passes because the mistake is recognizable and specific. Payoff passes because the ending supplies both a changed action and a consequence. This example does not establish that managers cause every missed deadline.
Editorial ratings (0–3): relevance 3, stakes 2, progression 3, payoff 3, opening clarity 2, pacing 2 provisionally. The pacing rating describes the written beats; vocal delivery has not been reviewed. These ratings are judgments, not predicted views.
Context and boundaries
The fixture declares processing coverage of 00:00–01:30. The Micro window includes all supplied segments, including the earlier weak candidate and the quiet gap. No additional resolution exists for the working-late passage in that supplied context.
Optional helper proposal: 00:29.850–00:57.300, from word s1-w0 through s3-w8, with 150ms lead and 300ms tail. This preserves the complete continuous passage. The helper does not verify silence or media identity, and the fixture's word timings are synthetic.
Hook and next step
Suggested overlay: “The deadline problem was me.” This is editorial copy, not a quotation. Review the actual source media and its boundaries before cutting. No footage has been watched, cut, rendered, approved or published in this demonstration.
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About this skill
A memorable sentence is not always a worthwhile clip. Clip Editorial helps your agent find passages that make sense to a new viewer and deliver a reason to care.
Start with your own timestamped podcast or interview transcript. The workflow surveys the source, inspects shortlisted moments with surrounding context, and tests each against fidelity, significance and payoff gates. The result is a ranked candidate board with source ranges, opening and closing lines, viewer value, weaknesses and review status. Weak candidates are rejected rather than dressed up with a misleading hook.
Included: editorial instructions, a story-review rubric, an editor handoff guide, fictional worked examples, input-format documentation, and an optional standard- library Python helper for compact transcripts, context windows and word-boundary proposals. Local helper support requires Python 3.10+ and access to packaged files. The instructions also support manual review of timestamped text without Python.
Developed through real local clipping projects and tested in a Codex/Windows workflow. Other agent runtimes and Agensi MCP delivery of executable resources have not been verified. This is editorial selection, not a full video editor: transcription, media playback, reframing and rendering are separate. No guaranteed virality, view forecasts, bundled videos, paid API dependency, or automatic posting.
Requires a supplied transcript; no speech-to-text model or media is bundled. Word-level refinement needs the documented JSON schema and word timings. Transcript review cannot verify delivery, speaker identity or safe audio cuts. Python helper is optional and requires Python 3.10+ with accessible supporting files. Agensi MCP executable delivery and other agent runtimes have not been tested. No view or virality guarantee.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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- Software
- Source mediaMedia player
- Optional
Python 3.10+
Python runs the optional local helper with the standard library. The media and player are for audiovisual boundary review and are not bundled.
Permissions
File Scopes
Helper reads supplied JSON and writes compact transcript, context-window, word-table and boundary-proposal files. Existing same-named outputs can be replaced; use a fresh output folder. No network requests, credential access, media rendering or publishing. Media transcription is a separate step.