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Glama

split

Idempotent

Split a timeline into shorts as new projects, reporting overlaps and unassigned spans, with a planning mode that writes nothing.

Instructions

Cut this timeline into shorts, each a new project beside this one.

For a footage dump: seed every recording (seed_timeline takes a list), clean it once (cut_by_transcript, verify), then split. Which shorts there are and where each starts is your reading of the transcripts. Each short is reel over its span, so everything reel reports comes back per short, and each also leaves out the recordings it does not use (clips_dropped).

overlaps (two shorts sharing material) and unassigned (timeline spans no short holds — a take missed stays in the dump) are reported, never refused: read both. This server cannot reach a short once it exists, by design; proofcut web --root <the dump's parent> lists them. plan=True resolves every short and creates nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intoNoThe directory the shorts are created in. Unset, the dump's own parent, so they sit beside it. A bound server takes no other.
pathNoThe project directory to act on. Omit it — the usual case — when this server is bound to a project (started as `proofcut -C DIR mcp`, or inside a project; `ping` says which): it then resolves to that one bound project, a relative path resolves against it, and a path outside it is refused by name. Unbound, `path` is the whole address and omitting it refuses rather than guessing.
planNoResolve the whole call and report what it would do, writing nothing. Prefer it over doing the thing and undoing it.
canvasNoThe shape to set on every short, e.g. `1080x1920` — one delivery shape for the batch. The dump keeps its own.
shortsYesEvery short, in order: `{name, from, to}` where `from` is its first word and `to` its last, each `{clip_id, word_index}` or `{clip_id, phrase}` (plus `occurrence` for a repeated phrase); or `{name, start, end}` in the render seconds `reel` takes. `name` is one directory name, created beside the dump, and must not exist.
confirm_suspectNoGo ahead even though a boundary word claims a suspect duration. Read the echoed words first — a suspect duration usually means whisper hid a retake inside that word, so the edge is not where it reads.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.43.0

TDQS

A4.9/5.0
Behavior5/5

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

The description goes beyond annotations by disclosing that `overlaps` and `unassigned` are reported, never refused, and that 'This server cannot reach a short once it exists, by design.' It also explains the `plan=True` behavior (resolves and creates nothing) and the `proofcut web` listing workaround. Annotations (readOnlyHint=false, destructiveHint=false) are not contradicted; these additional details significantly increase transparency for a mutation tool. No contradiction.

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?

The description is dense but every sentence carries information. It starts with the core action and then layers workflow, output behavior, and operational caveats. It is longer than typical but not wasteful. The structure effectively front-loads the primary purpose before diving into edge cases.

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?

Given the tool's complexity (6 params, 1 required, nested objects in `shorts`, and an output schema), the description covers all essential aspects: workflow, parameter semantics, boundary conditions (suspect durations), reporting of overlaps/unassigned, post-split accessibility, and dry-run. An agent has everything needed to invoke it correctly, including fallback listing via `proofcut web`.

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

Parameters5/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds substantial meaning beyond the schema. It explains the `shorts` format in detail (word indices, phrases, occurrences, render seconds), clarifies `into` behavior (unset -> dump's parent, bound server restriction), and `path` binding semantics. The `plan` and `confirm_suspect` parameters are also contextualized with reasoning. This fully compensates for any ambiguity in the schema.

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?

The description opens with a specific verb and resource: 'Cut this timeline into shorts, each a new project beside this one.' It clearly states the tool's function and distinguishes it from siblings by describing the workflow context (footage dump) and mentioning related tools (seed_timeline, cut_by_transcript, verify). The purpose is unambiguous.

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?

The description gives explicit usage conditions: 'For a footage dump: seed every recording... clean it once... then split.' It also clarifies the decision point ('Which shorts there are and where each starts is your reading of the transcripts') and recommends dry-run with `plan=True`. No alternative tools are named, but the workflow context is precise enough for an agent to know when to use this tool.

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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