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Get best performing posts

get_top_publications
Read-only

Rank social posts by a selected metric to reveal top content performance over a date range. Use engagement to compare across networks, since each network tracks different actions.

Instructions

The best performing posts of a range, ranked by one metric. This is the tool for 'what worked?'. Networks measure different things, so a ranking by impressions silently leaves out the networks that have none — rank by engagement to compare across all of them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
metricNoWhich metric to rank by. Defaults to engagement, the one every network reports.
to_dateNoISO 8601 date.
from_dateNoISO 8601 date. Defaults to the last 30 days.
id_organizationNoThe PlanVortex organization id. Optional.
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral nuance beyond annotations: rankings by impressions silently omit networks that report no impressions, and engagement is the safe cross-network ranking metric.

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 tight sentences: the first states the core behavior and scope, the second positions the tool and delivers the key metric caveat. No filler or redundancy.

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 all five parameters optional and documented in the schema, and annotations covering the read-only behavior, the description gives enough context for selecting and invoking the tool. It could add a note about the return shape or limit semantics, but nothing here is misleading or critically missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 80%, so the schema already documents most parameters. The description adds meaningful semantic insight by explaining why the metric choice matters (engagement is comparable across networks, impressions are not), which goes beyond the schema's plain descriptions.

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?

The description clearly identifies a specific action and resource: retrieve the best-performing posts for a date range, ranked by one metric. It is easy to tell apart from list_publications and get_publication_stats by meaning, though it does not name a sibling or an exclusion explicitly.

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?

It gives explicit situational guidance: 'This is the tool for what worked?' and even advises how to choose the metric (engagement for cross-network comparison). It does not name alternatives or state when not to use it, so it stops short of a 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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