edit_from_transcript

shallow

ai.weftly/weftly · Verify this server

Cut and re-assemble a video from an edited copy of its own word-level transcript — the text-editing counterpart to clips_from_job's timestamp-based cutting. Operates on a parent job (find_clips, summarize, or video transcribe) that has a word-level transcript; possessing the parent `source_job_id` is the capability, no upload step. Get the editable text first via get_job_status(job_id, format: "edit") or the download route — one `[NNNN]`-marked line per sentence — then edit it in any text editor: delete words or whole lines, move whole lines, but do not add or change a word (a marker used twice, or any added/changed word, invalidates the whole edit and is rejected before payment). Two-call flow: (1) call with `source_job_id` + the full edited text as `edited_transcript` (sent inline, max 262144 UTF-8 bytes) + optional `title` to receive {job_id, payment_challenge} — an invalid edit is rejected here, before any charge, with the exact failing lines; (2) pay via MPP (Tempo USDC) or open the Stripe Checkout `payment_url` in a browser, then call again with `job_id` + `payment_credential` to start processing. Flat price: $1.00 — see /.well-known/mpp.json for the Tempo USDC rate. Up to 300 cuts and 60 minutes of output per call; repeated phrases match their first occurrence, left to right. Outputs: role `clip-video` (the edited video), plus `clip-srt` and `clip-words` re-timed to match the edit. Source must still be in storage (72h TTL for find_clips parents, 24h elsewhere — check `expires_at` from get_job_status on the parent). Use whenever the edit is easier to describe in text than in timestamps — tightening a clip or a short segment by deleting filler words and tangents, or reordering a handful of sentences; use `extract_clip` (via clips_from_job) instead when you already know the exact start/end seconds you want. Retrying with `job_id` alone recovers the current state. A rejected edit creates no job, so show its errors to the user from the response that returned them. Failed jobs auto-refund.

100.0/100

1 trials · measured 1 day ago

edit_from_transcript scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against ai.weftly/weftly, measured 6 Oct 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
self-provisionable
Category
Finance & compliance
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-10-06100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

Embed this score

Available for every tool, scored or not — not a verification perk. Always links back to this page.

Vouch score: edit_from_transcript
[![Vouch score](https://vouch.tools/api/tools/dac3e3f1-5fc2-46dd-858b-38da412cb00a/badge.svg)](https://vouch.tools/tools/dac3e3f1-5fc2-46dd-858b-38da412cb00a)
edit_from_transcript — Vouch