betterpost_hide_storyHides a story so generation ignores it. Reversible with unhide_story.
| Name | Required | Description | Default |
|---|---|---|---|
| storyId | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| hidden | Yes | ||
| storyId | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / tokenRemoved value: -{
- "description": "Your saved BetterPost token from a prior call (demo `bp_demo_…` or paid `bp_live_…`). Reuse the same token on every call and across conversations; omit only on the very first call to be issued a free demo token. Paid users may instead pass the key in the server URL (?key=…) or an Authorization: Bearer header.",
- "type": "string"
-}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate idempotentHint=true and destructiveHint=false. The description adds that the action is reversible, providing 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 extremely concise (7 words) and front-loaded with the action. Every sentence serves a purpose: stating the action and noting reversibility.
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's simplicity (1 parameter, no nested objects) and presence of an output schema, the description adequately covers the essential purpose and reversibility. It could add a bit more detail about the hiding mechanism, but it's sufficient for an agent.
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?
The input schema has one parameter (storyId) with 0% schema description coverage. The description does not mention the parameter at all, failing to add meaning beyond the schema. It should specify that storyId is required and what it represents.
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 'hides' and the resource 'story', and specifies the effect 'so generation ignores it'. It also distinguishes from the sibling 'unhide_story' by noting reversibility.
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 indicates when to use (to hide a story) and mentions the alternative for reversal (unhide_story). It does not explicitly state when not to use it, but the context is clear.
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.