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Find the best clips in a long video

plan_clips

Ignix's clip editor: from the TRANSCRIPT of a long video (a live, a podcast, a webinar, a talk) grouped in sentences, it picks the moments that work on their own as reels (15-60 s each), ranked, each with start/end seconds, an on-screen hook, a caption and hashtags. Up to 2 hours. Spends 30 AI credits + 4 per started minute. OPTIONAL: by default you pick the clips yourself following get_edit_playbook (free) — call this only when the user asks for Ignix's picker. To edit one video as a single piece (captions, zooms, hook) use plan_video_edit. SPENDS AI CREDITS ONLY WITH confirm: true. Call it first without confirm: nothing runs and nothing is charged, you get the quote (what it will do and the credits). Tell the user, in your own words, exactly that — including the options you chose, so they can change them — and wait for a clear yes before calling again with the same arguments and confirm: true. One yes covers the plan they approved (e.g. every line of an approved voice-over with the chosen voice); anything new or different needs a new yes.

Input Schema

NameRequiredDescriptionDefault
countNoHow many clips the user wants (1-8). Omit to let the editor decide.
confirmNotrue ONLY after the user said yes to the quote (what it does and the credits). Without it nothing runs and nothing is charged.
requestYesWhat the user wants (e.g. "the best moments for Instagram", "the 3 most practical tips").
languageNoTwo-letter language (es, en…). Optional.
platformNo
sentencesYesThe whole transcript as sentences in order: { s: start second, e: end second, t: text }. At least 3.
durationSecYesLength of the video in seconds (10 to 7200).
workspaceIdNoWorkspace to work on (an id from list_workspaces). Not needed when this connection is tied to one workspace, or when you pass an account: the account's workspace is used.
idempotencyKeyNoOptional. A unique id for this action (16-128 chars: letters, digits, _ : . -). If you are unsure whether a call went through (timeout, network error), repeat it with the SAME idempotencyKey and the same arguments: you get the original result and nothing is done twice.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the annotations (readOnly=false, destructive=false, openWorld=true) by disclosing the cost model (30 credits + 4 per started minute), the 2-hour ceiling, and the two-call quote/confirm safety flow where the first call 'nothing runs and nothing is charged'. That is exactly the kind of spend and side-effect disclosure an agent needs before invoking.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core behavior and cost before the routing and confirm details, and nearly every sentence carries operational weight. Slight waste in the trailing 'one yes covers the plan they approved (e.g. every line of an approved voice-over with the chosen voice)' example, which belongs to a voice-over tool and adds noise here.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description compensates by enumerating the return payload (ranked clips with start/end seconds, hook, caption, hashtags). For a 9-parameter credit-spending tool with no annotations covering cost, the description supplies limits, cost, prerequisites and the approval protocol — nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 89%, so the baseline is 3, but the description adds real meaning: clip length bounds (15-60 s), the 2-hour duration limit, the ranked output shape tied to count, and a full semantic explanation of confirm as a two-call approval gate. Minor gap: it never mentions the request, platform, language or idempotencyKey parameters, though the schema covers them adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: it picks ranked standalone moments (15-60 s reels) from a sentence-grouped transcript, returning start/end seconds, hook, caption and hashtags. It also explicitly distinguishes itself from plan_video_edit (single-piece edit) and from the default get_edit_playbook flow, so an agent can route correctly without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when/when-not: 'by default you pick the clips yourself following get_edit_playbook (free) — call this only when the user asks for Ignix's picker', plus the alternative plan_video_edit for a single-piece edit. The mandatory confirm-then-quote protocol is spelled out step by step, including what to tell the user and when a new approval is needed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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