AT Protocol MCP Server

analyze_account

Read-only

Analyze a Bluesky account's engagement, network health, or posting strategy using sampled posts and connections. Read-only; requires authentication.

Instructions

Analyze a single account along one dimension. Requires authentication (app password). Read-only: performs no writes. One account-analysis tool: pick a dimension. For topic/search-based influencer discovery use find_influential_users instead. Subject to per-tool rate limiting.

Input Schema

TableJSON Schema

Name	Required	Description
`actor`	No	Handle or DID to analyze. Defaults to the authenticated user when omitted.
`dimension`	Yes	Which analysis to run: 'engagement' = recent-post performance; 'network' = follower/following graph health; 'strategy' = posting recommendations.
`limit`	No	How many recent posts to sample for engagement analysis (1–100, default 50).
`maxSampleSize`	No	How many connections to sample for network analysis (default per old behavior).
`includeReplies`	No	Engagement: include replies in the sampled author feed (default true).
`includeFollowers`	No	Network: sample the followers graph (default true).
`includeFollows`	No	Network: sample the follows graph (default true).
`analyzePosts`	No	Strategy: how many recent posts to analyze (10–100, default 50).
`includeTimingAnalysis`	No	Strategy: include best-posting-time analysis (default true).
`includeTopicAnalysis`	No	Strategy: include topic/keyword analysis (default true).

Output Schema

TableJSON Schema

Name	Required	Description
`success`	Yes	Whether the analysis succeeded.
`dimension`	Yes	Which analysis was run.
`actor`	No	network/strategy dimensions: the DID or handle that was analyzed.
`summary`	No	engagement dimension: aggregate statistics over the sampled posts (reposts of other authors excluded).
`topPosts`	No	engagement dimension: up to 10 posts ranked by total engagement.
`network`	No	network dimension: headline follow-graph counts for the account.
`analysis`	No	Dimension-specific analysis: graph classification for 'network', post-performance statistics for 'strategy'.
`insights`	No	Dimension-specific insights: structured content patterns for 'engagement', human-readable strings for 'network'.
`recommendations`	No	Dimension-specific recommendations: actionable strings for 'engagement', a structured plan for 'strategy'.

Tool Definition Quality

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by mentioning authentication and per-tool rate limiting, which are not covered by annotations. It reinforces the read-only nature without contradiction.

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?

Concise, with three sentences that front-load the purpose and immediately provide key usage guidance. No wasted words; each sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists (not shown but referenced) and annotations cover safety, the description sufficiently covers purpose, authentication, read-only nature, sibling differentiation, and rate limiting. It is complete for a well-annotated tool.

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 coverage is 100%, so the description does not need to add much. It provides a brief overview of dimensions but does not add meaning beyond the schema descriptions. Baseline 3 is appropriate.

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 the tool analyzes a single account along one dimension, with a specific verb and resource. It distinguishes itself from the sibling find_influential_users by noting it is for topic/search-based discovery, while analyze_account is for single-account analysis along a chosen dimension.

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

Usage Guidelines5/5

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

Explicitly states when to use (single-account analysis along a dimension) and when not (use find_influential_users for influencer discovery). Also specifies authentication requirement and read-only nature, providing clear context for agent decision-making.

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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