set_posting_cadenceSet how many articles per week the operator actually publishes (1-14). Sizes the pitch report’s 90-day content sequence; read back via get_project.postsPerWeek.
| Name | Required | Description | Default |
|---|---|---|---|
| context | Yes | One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose. | |
| projectId | Yes | ||
| postsPerWeek | 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: -[
- "projectId",
- "postsPerWeek"
-]New value: +[
+ "projectId",
+ "postsPerWeek",
+ "context"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, so the description is not required to restate that this mutates state. It adds value by disclosing the downstream effect on the pitch report sequence and the read-back path via get_project.postsPerWeek, which helps the agent understand consequences beyond the mutation itself.
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?
Two sentences with no filler: the first states the core action and range, the second gives the effect and read-back mechanism. The most important information is front-loaded and every clause earns its place.
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 three-parameter mutation with no output schema, the description gives the operation, the domain-specific range, the downstream impact, and how to verify the value afterward. The main missing piece is more explicit usage guidance, but the tool is simple enough that an agent can act on this definition.
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 33%, so the description should compensate for the undocumented parameters. It clarifies postsPerWeek's 'actual publishing' semantics and range, but gives no added guidance for projectId or context; context is left entirely to the schema, and projectId is not addressed at all in the description.
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 states a precise verb and resource: setting the operator's actual articles-per-week (1-14), and immediately explains why it matters by saying it sizes the pitch report’s 90-day content sequence. It is clearly distinguishable from sibling setters like set_opportunity_status or set_excluded_terms.
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 phrase 'actually publishes' implies this is for the operator's real cadence rather than a target or plan, and the 90-day sequence consequence gives useful context. It stops short of explicitly saying when not to use it or naming alternatives, but the intended context is fairly 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.
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.