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record_decisions

Save per-episode workflow answers—clip count, duration, captions, language, thumbnails, delivery, notes—keyed to the video path and size so future runs reuse them and skip repeated questions.

Instructions

Record per-episode workflow decisions (clip count, clip duration range, caption style, captions on/off, language, whether thumbnails are wanted, delivery target, free-form notes) so later runs against the same video never ask the same question twice. Keyed by the video's path + file size, not by session, so these answers survive a new episode overwriting ui-state.json. Pass only the fields you have an answer for; existing answers are preserved unless explicitly overwritten. get_ui_state lists any fields still unanswered as open questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoFree-form notes that don't fit another field
languageNoThe episode's spoken language
clip_countNoHow many clips to produce
video_pathYesThe episode's source video path (same path used with set_video/transcribe_podcast)
caption_styleNo
delivery_targetNoWhere clips are headed, e.g. youtube_shorts, tiktok, instagram, export_only
captions_enabledNoWhether clips should have captions burned in at all
clip_duration_maxNoMaximum target clip duration in seconds
clip_duration_minNoMinimum target clip duration in seconds
thumbnails_wantedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.8.0

TDQS

A4.1/5.0
Behavior4/5

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

No annotations, so the description must carry behavior and it mostly does: it discloses the keying strategy (video path + file size, not session), the persistence behavior across ui-state.json overwrites, and the partial-update merge semantics. It doesn't cover permissions or failure modes, but the core behavioral traits are unusually well disclosed.

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?

Three dense but purposeful sentences, front-loaded with the purpose before the keying and partial-update mechanics. No obvious filler, though the parenthetical field list is long.

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

Completeness4/5

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

For a 10-param mutation tool with no annotations and no output schema, the description covers purpose, persistence model, update semantics, and a sibling pointer. The main omission is what the call returns and any permission requirements.

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

Parameters3/5

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

Schema coverage is 80%, so most parameters are already documented. The description lists the categories of decisions but adds little per-parameter meaning beyond the schema, which already describes fields like video_path, clip_count, and notes. Baseline 3 is appropriate.

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 (record) and resource (per-episode workflow decisions), then enumerates exactly which decision fields are covered. It distinguishes itself from siblings like get_ui_state by naming it as the read counterpart.

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

Usage Guidelines4/5

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

Explains the why (so later runs never re-ask) and the interaction model (pass only fields you have; existing answers preserved). It routes to get_ui_state for unanswered fields. It does not explicitly say when not to use it, but the context is clear.

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