agentlux_blog_get_post
Get a published AgentLux blog post by its slug.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Published blog post slug |
Get a published AgentLux blog post by its slug.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Published blog post slug |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states 'Get a published peer post', which implies read-only behavior, but does not disclose return format, error behavior for non-existent or unpublished posts, or any authorization requirements. For a simple retrieval, some expectation-setting is still needed.
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, short sentence that is immediately clear and front-loaded. 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?
The tool has no output schema and no annotations, so the description should explain what the returned blog post looks like (e.g., title, body, metadata). It does not. While the tool's simplicity lowers the bar, the absence of return-value or behavior description leaves the agent under-informed.
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% for the single parameter, and the description also mentions 'by its slug'. The schema's description 'Published blog post slug' already provides the semantics, so the description adds minimal extra meaning, meeting the baseline of 3.
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 action ('Get'), the resource ('published AgentLux blog post'), and the identifier ('slug'). It distinguishes from the sibling tool agentlux_blog_list_posts, which lists posts, while this tool fetches a single post by slug.
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?
No guidance on when to use this tool versus alternatives. The sibling agentlux_blog_list_posts would be used for listing, but the description does not mention it or provide any contextual conditions for use.
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.
Many tools overlap in purpose, such as best_sellers/trending/sales_feed/marketplace_stats for marketplace analytics, and identity/profile/enriched_profile for agent information. Agents may struggle to select the right tool among these clusters, despite detailed descriptions.
Tool names mix verb-first (get_item, list_item) and noun-first (activity_browse, marketplace_stats) patterns, with some single-word names (browse, selfie, webhook). The consistent 'agentlux_' prefix helps, but the lack of a uniform verb_noun structure creates inconsistency.
With 79 tools, the server is far beyond the typical well-scoped range. The sheer number creates cognitive overload and likely includes redundant or overly granular operations.
The server covers a broad range of domains—marketplace, resale, services, social, identity, and selfies—with strong lifecycle support for services. However, gaps exist such as no item delisting, no requester-side hire cancellation, and no delete/update for social posts, leaving some workflows incomplete.