list_posts
List up to 20 recent posts belonging to a profile, with URLs usable in a quote.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| platform | Yes | ||
| username | Yes |
List up to 20 recent posts belonging to a profile, with URLs usable in a quote.
| Name | Required | Description | Default |
|---|---|---|---|
| platform | Yes | ||
| username | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / additionalPropertiesRemoved value: -falseDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds a concrete limit ('up to 20'), recency ('recent'), and the fact that returned URLs are directly usable in a quote, which is useful behavioral context beyond the annotations. No contradiction.
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 a single, front-loaded sentence with no filler. Every clause adds information: the list nature, the limit, recency, ownership, and the quoting use case.
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?
With only two simple parameters, read-only annotations, and no output schema, the description covers the core operation and the most relevant output characteristic (quote-usable URLs). It does not describe the full return shape, but this is a minor gap for such a scoped list operation.
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 0%, so the description must compensate for undocumented parameters. It indirectly references 'profile' for username but never explains the platform parameter or the exact meaning of username in that platform context. The enum on platform is self-explanatory, but the description leaves parameter semantics largely to inference.
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 uses a specific verb ('List') and names the resource ('posts') with clear boundaries: up to 20, recent, belonging to a profile. It also states the intended downstream use ('URLs usable in a quote'), which distinguishes it from the sibling list_services and other tools.
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 clearly conveys when to use this tool: when recent posts from a profile are needed, especially for quoting. It does not explicitly name counter-indications or alternatives beyond the phrase 'for a quote', but the context is clear enough given the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool maps to a distinct resource or action: profile lookup, post listing, service listing, quoting, order creation, payment, order status, and wallet balance. The only adjacent pair is list_services/get_quote, but their descriptions explicitly separate catalog pricing from exact quote calculation.
All tool names follow a consistent lowercase snake_case verb_noun pattern: get_* for single resources, list_* for collections, and create_order/pay_order for lifecycle actions. No mixed naming conventions or vague verbs appear.
Eight tools is well-scoped for a social media engagement purchasing server. Each tool covers a necessary step in the quote-to-delivery workflow without redundancy or unnecessary surface area.
The tool set covers the full lifecycle: discover services, inspect profiles/posts, get a verified quote, create an unpaid order, check wallet balance, pay, and track order status. No critical gap prevents an agent from completing the intended purchase flow.