atlas-social-mcp

Does 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 mentions 'AI adapts content per platform,' which hints at automated content modification, but doesn't cover critical aspects: whether scheduling requires specific permissions, if posts can be edited/canceled after scheduling, rate limits, error handling, or what the response looks like (since no output schema). For a mutation tool with zero annotation coverage, this is a significant gap.

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 extremely concise—two short sentences that are front-loaded with the core purpose. Every word earns its place: the first sentence defines the action, and the second adds a key behavioral trait (AI adaptation). There's no redundancy or fluff.

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 (a mutation tool with 7 parameters, no annotations, and no output schema), the description is incomplete. It lacks behavioral details (e.g., permissions, reversibility), usage context versus siblings, and output expectations. While the schema covers parameters well, the description doesn't compensate for missing annotation and output information, making it inadequate for safe and effective use.

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 7 parameters thoroughly (e.g., 'text' as content, 'platforms' as array, 'schedule_time' as ISO 8601). The description adds minimal value beyond the schema—it implies multi-platform support and AI adaptation but doesn't provide additional syntax, format details, or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

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: 'Schedule a social media post for a specific future date and time.' It specifies the verb ('schedule'), resource ('social media post'), and temporal scope ('future date and time'). However, it doesn't explicitly differentiate from sibling tools like 'post_now' (immediate posting) or 'generate_calendar' (calendar-related), though the scheduling focus is implied.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'post_now' for immediate posting or 'get_recent_posts' for retrieval, nor does it specify prerequisites (e.g., authentication, platform setup) or exclusions (e.g., scheduling limits). Usage is implied by the name but not explicitly stated.

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