atlas-social-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly describes the core behavior (immediate posting with AI adaptation) and lists supported platforms, which is valuable. However, it doesn't disclose important behavioral traits like authentication requirements, rate limits, error handling, or what happens when posting fails on some platforms. The description doesn't contradict annotations (none exist).

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 efficiently structured in two sentences: the first states the core functionality, the second lists supported platforms. Every element earns its place - the AI adaptation detail is crucial context, and the platform list helps users understand scope. No wasted words or redundant information.

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?

For a complex 8-parameter mutation tool with no annotations and no output schema, the description provides adequate but incomplete context. It covers the what (posting with AI adaptation) and where (platform list), but lacks information about return values, error conditions, authentication needs, or platform-specific constraints (like Instagram requiring media). The 100% schema coverage helps, but behavioral aspects are underspecified.

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?

Schema description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it mentions platform support and AI adaptation (which relates to the 'adapt_per_platform' parameter), but doesn't provide additional meaning for parameters like 'brand_name' or 'media_url'. This meets the baseline for high schema coverage.

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 clearly states the tool's purpose with a specific verb ('Post content') and resource ('to social media platforms immediately'), distinguishing it from siblings like 'schedule_post' (immediate vs scheduled posting) and 'generate_calendar' (planning vs execution). It explicitly mentions the AI adaptation feature, which adds specificity beyond basic posting.

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?

The description provides clear context for when to use this tool: for immediate posting with AI adaptation across platforms. It implicitly distinguishes from 'schedule_post' (immediate vs scheduled) and 'get_recent_posts' (posting vs retrieval), but doesn't explicitly state when NOT to use it or name alternatives like 'schedule_post' for delayed posting scenarios.

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