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ZeroWidth Workbench

Compile a sentence into a Task plan

workbench_tasks_compile

Runs the compiler over a sentence and returns the PROPOSED plan (or repair-grade problems — fix by refining the sentence with the user, not by guessing). Nothing persists. Present the proposal in plain terms: which clauses run flows, which you (zv1) will handle, who decides, what the compiler noted. Then iterate or freeze. Compile may take ~15s.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskIdNoThe task this sentence belongs to, when compiling an edit — keeps it out of the child-task candidates.
sentenceYesThe sentence to compile.
workspaceNoWorkspace slug. Personal tokens with no default workspace MUST pass this; tokens with a default can override per call. Ignored for workspace API keys.
approvalIdNoRe-call with the approvalId from a needs_confirmation response after the user approves.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Adds context annotations do not carry: nothing is persisted, the call can return repair-grade errors rather than a plan, and it may take ~15s. There is mild tension between “Nothing persists” and readOnlyHint=false, but the schema's approvalId / needs_confirmation flow plausibly accounts for that, so this reads as added detail rather than a 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?

Front-loaded: the first sentence gives the action and the return shape, followed by guidance, then the latency note. Dense but every clause is doing work; the “which you (zv1) will handle” phrasing is a touch cryptic but purposeful.

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 usefully characterizes the return (proposed plan, compiler notes, repair problems) and the iteration/approval loop, plus latency. It stops short of explaining the plan's structure or the confirmation response shape, but is sufficient to call and act on it.

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 description coverage is 100%, so each of the four parameters (taskId, sentence, workspace, approvalId) is already documented in the schema. The description only reinforces the sentence-refinement loop and adds nothing about formats or limits, so the baseline 3 applies.

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 — “runs the compiler over a sentence” — and names the artifact it returns: the PROPOSED plan (or repair-grade problems). The “Nothing persists” clause and the “iterate or freeze” ending implicitly separate it from workbench_tasks_freeze/workbench_tasks_create, which commit state.

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?

Gives clear context (“fix by refining the sentence with the user, not by guessing”, “Then iterate or freeze”) and tells the agent what to do after the call. It does not name the sibling that commits the plan (freeze/start), so a little inference is still required.

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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