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SelfPy

science-ai-mcp-server

Start Article Writer Pipeline

start_writer_pipeline

Enqueue a writer-pipeline job for an existing WriterSession; returns a jobId immediately for progress tracking.

Instructions

Enqueue a writer-pipeline job for an existing WriterSession. Returns immediately with a jobId; the orchestrator-worker claims it within ~5 seconds. Default section is step_7_5 — the auto-chain that replaces the three buttons in Step 7.5. Use get_writer_pipeline_status to poll until status is 'done', 'failed', or 'aborted'. Uses Science AI Journal credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sessionIdYesWriterSession id you already own. Create one via the web UI at /writer first; the MCP server does not own the session-creation flow today.
sectionNoWhich section to run. Default 'step_7_5' (the code-search → adapt → verify → simulate chain).
languageNoSimulation language override (python | r | matlab | ...).
forceNoIf true, abort any existing queued/running job for this (sessionId, section) and enqueue fresh.
Behavior4/5

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

Discloses immediate return with jobId, ~5s claim time, default section, credit usage. Schema adds force behavior. No annotations exist so description carries full burden, and it does well.

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?

Four sentences, front-loaded with key action, no filler. Efficient and clear.

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?

Covers enqueue action, return type, timing, default, credits, and references sibling for polling. Lacks error handling details but sufficient for a simple tool with clear sibling.

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 covers 100% parameters with descriptions. Description adds minimal value: default section elaboration. 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?

Clearly states the action (enqueue a writer-pipeline job) and resource (existing WriterSession). Distinguishes from sibling get_writer_pipeline_status by describing the polling pattern.

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?

Provides explicit context: requires existing WriterSession, default section, and references sibling for polling. Schema description adds prerequisite (create session via web UI). No explicit exclusion for concurrent jobs, but force parameter is described.

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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