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cameronrye

AT Protocol MCP Server

analyze_moderation_status

Read-only

Evaluate moderation status of a user or post to determine safety before rendering content. Returns content labels, moderation decisions, and personal blocks or mutes.

Instructions

Analyze moderation status of a post or user. Returns content labels, moderation decisions, and personal moderation state (blocks, mutes). Subject can be a DID (for users) or AT-URI (for posts). Works without authentication; richer with auth. Use this tool to evaluate safety before rendering content; use block_user or mute_user to act on the results. Subject to per-tool rate limiting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subjectYesDID of a user account (e.g. did:plc:abc123) or AT-URI of a post (at://did/app.bsky.feed.post/rkey) to analyze.
includeLabelsNoWhether to fetch and include content labels in the response (default true). Set to false to skip label fetching for a faster call.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successYesWhether the analysis completed successfully.
subjectYesThe DID or AT-URI that was analyzed.
subjectTypeYes"user" when subject is a DID; "post" when subject is an AT-URI.
moderationYesRaw moderation state for the subject.
analysisYesDerived safety analysis based on labels and moderation state.
Behavior5/5

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

Annotations declare readOnlyHint=true and openWorldHint=true; description adds that it works without auth but richer with auth, and mentions rate limiting. No contradictions.

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?

Four sentences, each adding value: purpose, returns, subject types, auth, rate limiting, usage guidance. No wasted words.

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?

With output schema, return values are covered. Description covers subject types, auth dependency, rate limiting, and relationship to sibling tools. Complete.

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

Parameters4/5

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

Schema coverage is 100%, so baseline 3. Description adds meaning: explains subject format (DID or AT-URI) and includeLabels effect (faster if false). Above baseline.

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?

Description clearly states 'Analyze moderation status of a post or user' and lists return types. It distinguishes from sibling tools like block_user and mute_user.

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 says 'Use this tool to evaluate safety before rendering content; use block_user or mute_user to act on the results.' Provides clear usage context and alternatives.

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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