add_article_suggestionAdd a bare article suggestion to a content plan (title + optional intent and reasoning). For richer input that produces a brief-ready suggestion, use create_article_suggestion_with_input.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | ||
| intent | No | ||
| context | Yes | One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose. | |
| projectId | Yes | ||
| reasoning | No | ||
| contentPlanId | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / contextAdded value: +{
+ "description": "One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose.",
+ "type": "string"
+}Input schema / requiredPrevious value: -[
- "contentPlanId",
- "projectId",
- "title"
-]New value: +[
+ "contentPlanId",
+ "projectId",
+ "title",
+ "context"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate readOnlyHint=false and destructiveHint=false, and the description reinforces a non-destructive mutation by saying 'add to a content plan.' It does not disclose extra behavioral details such as duplicate handling or resulting suggestion state, but the bar is lowered by the annotations and no contradiction exists.
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 two sentences with no filler. The core action is front-loaded and the sibling routing is saved for the second sentence, making it easy to scan and act on.
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 description is adequate for a simple create-like operation, especially with the sibling routing and annotations. However, it omits guidance about the required context parameter, which is unusual enough that an agent may misinterpret it without reading the schema carefully; this leaves a real but not fatal gap.
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 only 17%, so the description must compensate; it only explains title, intent, and reasoning. Required parameters like contentPlanId, projectId, and especially context are not clarified in the description, and the context field's unusual semantics (operator's goal, not tool's purpose) is left entirely to the schema.
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 opens with a specific verb and resource: adds an article suggestion to a content plan, and clarifies the payload as title plus optional intent and reasoning. It also distinguishes itself from create_article_suggestion_with_input, so an agent can immediately tell the two closest siblings apart.
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 explicitly names the alternative tool, create_article_suggestion_with_input, and gives the decision criterion: use that tool for richer input that produces a brief-ready suggestion. This clearly implies when to use the current tool and when to route elsewhere.
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.
Most tools target a distinct resource and action, and the descriptions carefully cross-reference close alternatives (e.g., add_article_suggestion vs create_article_suggestion_with_input vs accept_idea). A few brief/read variants like get_article_brief, get_write_handoff, and download_brief_markdown could still be confused despite helpful explanations, so the set is not perfectly unambiguous.
Tool names follow a highly consistent verb_noun snake_case pattern throughout: get_*, list_*, create_*, update_*, set_*, add_*, delete_*, start_*, expand_*, etc. Even the less common names like lint_draft and remap_asset are still clear verb_noun constructions.
At 57 tools, this far exceeds the 50+ extreme threshold for a single MCP server. Even for a broad content workflow, the surface is overwhelming and would benefit from consolidation or splitting into focused servers.
The tool set covers the full content lifecycle: project setup, research runs, opportunity clustering, suggestion creation, brief generation, drafting, linting, publishing, reporting, and account management. Minor gaps exist—destinations and projects cannot be deleted via MCP, and there is no direct update for article suggestion metadata—but these are workable via the web UI or existing tools.