Skip to main content
Glama
rimmade

syncly-dataset-mcp

by rimmade

get_ranked_posts

Retrieve up to 100 posts from a dataset, ranked by engagement count, likes, comments, shares, or creation date. Apply filters for platform, brand, sentiment, category, and date range.

Instructions

Return posts ranked by a metric or recency (max 100, descending).

Args: query_id: Dataset ID from list_data_queries rank_by: Metric to rank by. One of: engagement_count, like_count, comment_count, share_count, created_at filters: Dict with optional keys: platform, brand, sentiment, category, date_from, date_to limit: Max results, up to 100

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_idYes
rank_byNoengagement_count
filtersNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It discloses ranking direction, limit, and the need for a query_id. However, it does not explain behavioral traits like idempotency, error handling, or whether results are paginated, leaving gaps for a read-like operation.

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?

The description is front-loaded with the main purpose and uses a structured args list. It is efficient but slightly verbose with blank lines. Overall, it earns its length without being overly wordy.

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?

Given the presence of an output schema, the description need not detail return values. It covers core functionality, parameters, and a prerequisite. Minor omissions like error cases or pagination details prevent a perfect score.

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

Parameters5/5

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

The input schema has 0% description coverage, but the description fully compensates by explaining each parameter: query_id's source, rank_by's options, filters' keys, and limit's maximum. This adds critical semantic meaning beyond the bare schema types.

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 states the tool returns posts ranked by a metric or recency, with specific constraints (max 100, descending). It is a specific verb+resource pair, but does not explicitly differentiate from sibling tools like search_posts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus siblings such as search_posts or safe_query. The description implies a prerequisite (query_id from list_data_queries) but lacks explicit when-to-use or when-not-to-use instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rimmade/syncly-dataset-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server