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ismail: agent DAW (MCP server)

Stage Say

stage_say

Sends captions or spoken messages to a performer, queuing them by scene and showing sender-styled text in desktop or VR so agents can deliver cues without disrupting takes.

Instructions

Tell the person something (page command: say). Desktop: a caption, one at a time, queued, shown only while the tab is visible. VR (or voice=True on the desktop): also spoken by Kokoro (voice_name picks the voice; the server default is af_heart), and in VR shown for min(120, 25 + 0.8 x words) seconds as a caption panel. A line that waited 20 s or more in the queue is captioned, not spoken; 60 s or more, no VR panel either. Page replies {captions_ahead}, plus {spoken: false, stale_s} for a stale line. Emits: voice_spoken, voice_hushed (the person started a voice note mid-line), voice_dropped, voice_error, and in VR panel_shown and panel_closed. sender= your name as the person should see it (e.g. "crossroads film"): the caption and its VR card say it, in that name's colour, on that name's side of their body. While the person performs (someone follows them) the line is shown, not spoken, since it would be in the recording (page replies held: ...); aloud=True speaks it anyway (an answer they asked for).

Input Schema

NameRequiredDescriptionDefault
textYes
aloudNo
sceneYes
voiceNo
senderNo
secondsNo
voice_nameNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.4.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description is remarkably transparent. It discloses complex behavioral logic like queue management (what happens at 20s vs 60s), specific rendering logic (caption duration formulas), and a list of emitted events, which is crucial for debugging and state tracking.

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

Conciseness3/5

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

The description is highly technical and dense, functioning more like a documentation block than a concise tool definition. While every sentence is information-rich, the overall length and lack of clear structural breaks reduce its immediate scannability for an AI agent.

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 lack of annotations and high complexity, this description is maximally complete. It details operational context (Desktop vs VR), timing, state transitions, and how parameters influence the final user experience.

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?

Since schema coverage is 0%, the description must carry the burden. It provides critical semantic information missing from the schema, such as explaining 'voice_name' and defining the purpose of 'sender' (who the person sees it from).

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

Purpose4/5

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

The purpose is clearly stated as telling a person something (page command: say). It is a specific communication action, clearly distinguishing itself from scene manipulation or audio playing tools in the large sibling list.

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 provides extensive usage guidance covering multiple scenarios: desktop visibility constraints, VR spoken vs captioned modes, behaviors for stale messages (20s/60s), and the specific context for using 'aloud=True' (when an answer is requested).

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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