betterpost_add_storyManually imports a story you read about from its URL (pinned relevance, flagged is_manual) so generation can draw on it.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| title | No | ||
| summary | No | ||
| projectId | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| storyId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond the annotations: it indicates the story is 'pinned' and 'flagged is_manual', and that the import is from a URL. Annotations already mark it as non-read-only, so the write nature is consistent. The description provides useful additional traits without contradicting annotations.
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 sentence that is concise and front-loaded. It communicates the core purpose without any wasted words or unnecessary details. It earns its place by being direct and informative.
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 tool has 4 parameters (2 required) and no schema descriptions, the description is somewhat incomplete. It does not clarify behavior in edge cases (e.g., duplicate URL, project existence) or mention output. However, an output schema exists, reducing the need to explain return values. Still, more context on prerequisites and behavior would improve completeness.
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. While it hints at the 'url' parameter (import from URL), it does not explain the meaning or usage of 'projectId', 'title', or 'summary'. These are left to the agent to infer, which is insufficient given the lack of schema descriptions.
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 verb 'imports', the resource 'story', and the method 'from its URL'. It also explains the effects (pinned relevance, flagged is_manual) and the purpose (so generation can draw on it). This distinguishes it from sibling tools like betterpost_list_stories or betterpost_hide_story.
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 implies when to use the tool: when you have a story you read about and want to manually import it. However, it does not explicitly state when not to use it or mention alternatives among the 21 sibling tools. The context is clear but lacks exclusionary guidance.
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.
Every tool has a clearly distinct purpose—project management, source and story handling, content generation, settings, and usage—with no overlapping functionality. The descriptions clearly delineate when to use each tool.
All tools follow the consistent pattern 'betterpost_<verb>_<noun>', making the set predictable and easy to navigate. The naming convention is uniform throughout.
With 23 tools, the server covers a comprehensive content generation workflow without being overwhelming. Each tool serves a necessary function, and the count feels well-scoped for the domain.
The tool surface covers the full lifecycle of project management, source acquisition, story curation, content generation/derivation, and settings configuration. There are no obvious gaps that would cause an agent to fail in typical use cases.