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mathieubernardi

meta-mcp-py

top_ig_posts

Rank Instagram posts by reach, likes, comments, saves, shares, or total interactions to identify top-performing content and inform your content strategy.

Instructions

Classe les publications Instagram par performance.

sort_by : reach, likes, comments, saved, shares ou total_interactions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sort_byNoreach
ig_user_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the transparency burden. It conveys a non-mutating ranking behavior and enumerates acceptable metrics, but it does not disclose whether only top-N posts are returned, any time-window constraints, required permissions, or how ties or missing metrics are handled.

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 short, front-loaded sentences: the first states the operation and the second clarifies the key parameter. There is no filler or repetition.

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?

An output schema exists, so return-value documentation is not required. The description still leaves gaps that matter for correct use: no explicit time window, no note that only the top N posts are returned, and no guidance on account scope beyond the implied ig_user_id.

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 adds important value for sort_by by listing the allowed values, which the schema does not provide as an enum. However, it says nothing about ig_user_id or limit, leaving those to be inferred from their names and schema defaults.

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 uses a clear verb ('Classe') and a clear resource ('publications Instagram'), and states the ranking criterion ('par performance'). It is distinguishable from siblings like list_ig_media or get_ig_media_insights, though it does not explicitly name a sibling to differentiate against.

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 intended use is implied: rank Instagram posts by a selected performance metric. The listed sort_by values give concrete guidance, but the description never says when to prefer this tool over alternatives such as get_ig_media_insights or get_ig_account_insights, nor does it state exclusions.

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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