Search Facebook posts to extract content and metadata from profiles, pages, groups, and marketplace listings for data analysis.
Performs facebook posts search
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "search_post"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action without any details on how the search works (e.g., pagination, rate limits, authentication needs, or what the output looks like). For a search tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded and appropriately sized for a simple tool, making it easy to parse quickly. Every word earns its place by stating the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a search operation, lack of annotations, no output schema, and many similar sibling tools, the description is incomplete. It doesn't explain what the search returns, how results are filtered, or behavioral aspects like performance or errors. For a tool in this context, more detail is needed to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add param info, but since there are no params, a baseline of 4 is appropriate as it doesn't need to compensate for any gaps. It's sufficient for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Performs facebook posts search' states the action (search) and resource (facebook posts), which is clear but vague. It doesn't specify what kind of search (e.g., keyword-based, filtered by date, etc.) or how it differs from sibling tools like 'search', 'search_groups_posts', or 'search_hashtag', which also search Facebook content. This lack of differentiation keeps it at a basic level.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools like 'search', 'search_groups_posts', and 'search_hashtag' that also perform searches, the description offers no context, prerequisites, or exclusions to help an agent choose appropriately. This omission leaves usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.