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shauryasa0

sprout-mcp

by shauryasa0

get_post_performance

Retrieve per-post analytics for posts created in a specific datetime range. Supports custom metrics (e.g., impressions, reactions) and fields (tags, links) for in-depth analysis.

Instructions

Pull post-level analytics for posts created in a datetime range.

Args: profile_ids: customer_profile_id values from list_profiles. Max 100. start_datetime: inclusive, YYYY-MM-DDTHH:MM:SS (e.g. 2026-06-01T00:00:00). end_datetime: inclusive, YYYY-MM-DDTHH:MM:SS (e.g. 2026-06-30T23:59:59). metrics: post metric keys, mostly prefixed lifetime. -- e.g. ["lifetime.impressions", "lifetime.reactions", "lifetime.comments_count"]. A few are unprefixed (e.g. video_length on Facebook and TikTok). Network-specific; call list_metrics for valid keys. fields: post attributes to include, e.g. ["created_time", "text", "perma_link", "post_type", "internal.tags.id", "internal.sent_by.email"]. timezone: ICANN tz name for bucketing, e.g. "America/Los_Angeles". sort: sort expressions, e.g. ["lifetime.impressions:desc"]. page: 1-based page to start from (50 posts per page by default). all_pages: follow pagination and concatenate the data arrays. max_pages: cap on pages fetched when all_pages is true.

Returns the API response verbatim -- one record per post, carrying whichever fields and metrics were requested. Useful for per-post label/tag analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
sortNo
fieldsNo
metricsNo
timezoneNo
all_pagesNo
max_pagesNo
profile_idsYes
end_datetimeYes
start_datetimeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden; it discloses pagination behavior (page, all_pages, max_pages), specifies that returns are 'API response verbatim', and clarifies parameter constraints like max profile_ids and datetime format.

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 well-structured with a summary line and organized Args section; it is slightly verbose but every sentence adds value.

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 10 parameters and the presence of an output schema, the description adequately covers return format ('API response verbatim') and usage context; minor gaps in edge-case behavior (e.g., empty results) 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?

Schema coverage is 0%, but the description fully compensates by detailing every parameter with examples, defaults, constraints, and usage notes (e.g., lifetime prefix for metrics, timezone format).

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 clearly states 'Pull post-level analytics for posts created in a datetime range', a specific verb-resource combination that distinguishes it from sibling tools like list_profiles and get_profile_metrics.

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 description provides context for when to use (e.g., for per-post analysis and pagination control) but does not explicitly mention alternatives or conditions to avoid using this tool.

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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