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Lazybird

by io.github.lazybirdai
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Generate a project's speech

generate_project_speech

Make speech for a project's voiceover blocks, using characters from the user's balance. By default only blocks without up-to-date speech; with regenerate, blocks that have speech too, made anew. Speech is made in the background: read_project shows each block's.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "projectId": "<projectId>"
    },
    "name": "generate_project_speech"
  }
}

Input Schema

NameRequiredDescriptionDefault
blockIdsNoThe blocks to make speech for; all when omitted
projectIdYesA project id from list_projects or create_project
regenerateNoAlso make speech anew for blocks that have it

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

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

Beyond the annotations, the description discloses three non-obvious traits: the operation spends the user's character balance, it runs asynchronously in the background, and results must be polled via read_project. That is precisely the kind of cost and lifecycle context annotations cannot convey.

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 short and front-loads the purpose, then the default/regenerate distinction. The final clause 'read_project shows each block's' is truncated and reads awkwardly, costing it clarity.

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?

With no output schema, the description correctly supplies the missing lifecycle information (background job, check via read_project). It could go further by saying whether a job identifier is returned or what happens if the balance is insufficient, but it is sufficient to invoke the tool correctly.

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 100%, so 3 is the baseline, but the description adds real semantics: it clarifies that blockIds scopes the job to specific blocks and explains what 'regenerate' does to blocks that already have speech. The only gap is that the interaction between an explicit blockIds list and regenerate is only implied.

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 description gives a specific verb+resource ('Make speech for a project's voiceover blocks') and adds the important billing note that it consumes characters from the user's balance. It does not explicitly distinguish itself from the sibling generate_speech, so an agent must infer that this is the project-scoped variant.

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?

It clearly states the default selection rule (only blocks lacking up-to-date speech) versus the 'regenerate' behavior, which is exactly the decision an agent needs to make. It also routes the agent to read_project for status, though it never names an alternative generation tool or states exclusion conditions.

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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