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Foliora Managed AI Search

List what Foliora proposes for a site

list_page_jobs
Read-onlyIdempotent

The page changes Foliora proposes for one owned site, highest impact first — the same list the customer's dashboard shows. Each row carries fix: the customer-facing state (Foliora is working / Your turn / Published / Verified live / Needs a hand), why there is no draft to act on when there is none, the live status of every finding it set out to fix, and nextAction. Use get_page_job to read a proposal in full before the customer decides.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteIdYes
statusNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobsYes

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?

The description adds substantial behavior beyond the readOnly/idempotent annotations: rows are sorted by impact, the list matches the customer dashboard, and each row includes the fix state, the reason a draft may be absent, live finding statuses, and nextAction. It also signals that the full proposal is available elsewhere, which helps the agent set expectations when invoking this list.

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?

Three sentences, each earning its place: the first establishes purpose, scope, and ordering; the second describes row semantics; the third names the follow-up tool. Important details are front-loaded and there is no filler or repetition.

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 an output schema and readOnly annotations present, the rich description covers sorting, row content, and the path to get_page_job. The main remaining gap is the meaning of the status parameter, which an agent would need to filter correctly. Otherwise the definition is complete for a read-only listing tool.

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%, so the description must compensate. It does clarify that the list is for 'one owned site', which maps to siteId, but it never explains the optional status enum ('proposed' vs 'all') or the default behavior. The description partially bridges the schema gap but leaves a meaningful parameter unexplained.

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?

The description opens with a specific verb and resource: 'The page changes Foliora proposes for one owned site.' It adds meaningful scoping ('highest impact first', 'same list the customer's dashboard shows') and distinguishes itself from the deeply related get_page_job sibling. There is no ambiguity about what this tool returns.

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 description clearly positions the tool as the list-level view and explicitly routes deeper inspection to get_page_job: 'Use get_page_job to read a proposal in full before the customer decides.' It does not enumerate exclusions for other siblings, but the main alternative is named and the context for choosing one over the other is clear.

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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