betterpost_remove_sourceRemoves a source from a project. Its already-gathered stories stay; the source is no longer fetched.
| Name | Required | Description | Default |
|---|---|---|---|
| sourceId | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| removed | 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?
The description adds value beyond annotations by specifying that existing stories are preserved and fetching stops. It aligns with the destructiveHint=true and idempotentHint=true annotations. No contradictions.
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, clear sentence with no wasted words. It is front-loaded with the action and quickly addresses the key behavioral nuance.
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?
For a simple removal tool with one parameter and an output schema, the description adequately covers the effect. It does not mention error conditions or return values, but the presence of an output schema may offset the latter.
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 schema has 0% description coverage, and the tool description does not mention the single parameter 'sourceId' or its meaning. The agent must infer from the tool name and schema pattern, but no additional semantic context is provided.
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 the specific verb 'removes' and identifies the resource 'source from a project,' which distinguishes it from sibling tools like betterpost_add_source. It further clarifies that existing stories are not removed, differentiating it from delete operations.
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?
While the description states the effect (stories stay, source no longer fetched), it does not explicitly provide when-to-use or when-not-to-use guidance. However, the context from sibling tool names and the clear behavioral outcome sufficiently imply usage.
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.