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Pipeline status

pipeline_status
Read-only

Where every live article and topic stands, in one read: approvalMode (human or agent, set by the workspace owner), the delivery destination or null, counts per stage, and one compact row per article. Stages in order: idea (topic without a SERP brief), researched (topic with a SERP brief), writing (scheduled and not written yet, no passing rules run on the current body, or failed; status and date tell these apart), review (passed the rules, waiting for approval), approved (ready; deliveredAt says whether the draft reached the destination), published (published from the seodraft app or marked published by the human). No bodies or briefs: get_post reads one article and list_topics the topic bank.

Input Schema

NameRequiredDescriptionDefault
workspaceIdNoThe workspace this call acts on, as listed by list_workspaces. Left out, the call uses the workspace the account is in right now.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only declare read-only, non-destructive, closed-world; the description goes well beyond by enumerating what is returned (approvalMode, destination or null, stage counts, compact article rows) and defining every stage and its ordering. It also clarifies deliveredAt semantics and explicitly excludes bodies and briefs, which is valuable since there is no output schema.

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 with the core purpose in the first clause, followed by dense but relevant detail. The long stage-definition sentence is justified because no output schema exists, though bullet-style structure would improve scanability.

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?

With no output schema and a read-only aggregate tool, the description carries the return-shape burden thoroughly: fields returned, stage definitions, ordering, and what is excluded. Combined with the fully documented optional parameter, an agent has everything needed to call it correctly.

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?

There is one optional parameter and schema description coverage is 100%, so the schema already fully documents workspaceId and its fallback behavior. The description adds no parameter-level detail, which is acceptable given the schema does the work, but it earns no credit above baseline.

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 resource and scope: a one-read view of where every live article and topic stands, including per-stage counts and per-article rows. It also names the sibling tools it is not (get_post for a single article, list_topics for the topic bank), so an agent can distinguish it immediately.

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?

The 'in one read' phrasing and the explicit routing away from article bodies/briefs ('get_post reads one article and list_topics the topic bank') give clear alternatives. It stops short of stating an explicit trigger condition like 'use before approving or scheduling', so it is not a full 5.

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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