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prompt_pipeline

Starts a durable prompt-engineering run—either full idea-to-prompt generation or optimize-only rewriting—and returns the next isolated-worker dispatch for the host to execute.

Instructions

Start a durable Full (idea → prompt) or optimize-only (existing prompt) run. Returns the next isolated-worker dispatch; the host executes it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
inputYes
prioritiesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare this is a non-read-only, non-destructive, non-idempotent, closed-world write. The description usefully adds beyond that: the run is 'durable', and the call returns a 'next isolated-worker dispatch' that 'the host executes' — a non-obvious async/dispatch contract. It stops short of saying what happens on re-invocation or how the run is later resumed/inspected.

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

Conciseness5/5

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

Two sentences, zero filler, front-loaded with the action and its two variants, then the return/dispatch contract. Nothing redundant with the name or schema.

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

Completeness3/5

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 explains the return value (a worker dispatch executed by the host), which is the key missing structured information. But for a durable, stateful run tool surrounded by pipeline_status/submit/pause/resume siblings, it omits how the run is tracked afterward and leaves 'priorities' unexplained.

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 0% across 3 params, so the description must carry the load. It does clarify mode (naming both enum values) and gives strong semantic framing for 'input' (an idea for full, an existing prompt for optimize-only), but the third parameter 'priorities' is never mentioned, leaving a gap.

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?

States a specific verb ('Start') and resource ('run') and enumerates the two modes with their inputs ('Full (idea → prompt)' vs 'optimize-only (existing prompt)'), so the agent knows exactly what happens. It does not, however, distinguish itself from close siblings like pipeline_submit or pipeline_status, so the agent must infer the split.

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

Usage Guidelines3/5

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

The parenthetical glosses for each mode implicitly tell the agent which mode to pick based on whether it has an idea or an existing prompt. There is no explicit when-to-use vs when-not guidance against the other pipeline_* siblings, so usage is only implied.

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