add_competitor_by_domainAdd a competitor to a project by domain (e.g. example.com). Marks the competitor as important or ignored on creation.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | ||
| context | Yes | One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose. | |
| projectId | Yes | ||
| importance | 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",
- "domain",
- "importance"
-]New value: +[
+ "projectId",
+ "domain",
+ "importance",
+ "context"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only say readOnly=false and destructive=false; the description adds that the tool creates a competitor and marks its importance at creation. It does not disclose duplicate-domain behavior, idempotency, or failure modes, so the behavioral picture is incomplete.
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 short sentences with no filler. The core action is front-loaded, and the side-effect detail about importance 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 mutation tool with four required parameters and no output schema, the description is adequate but lean. An agent can determine what to pass, but it has no guidance on return values, duplicate handling, or what happens if the project or domain is invalid.
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 25%, so the tool description carries weight. It clarifies that domain is a website address and that importance is set to 'important' or 'ignored' on creation. projectId is left mostly to inference, but the phrase 'to a project' anchors its meaning.
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 specific verb ('Add') and resource ('competitor to a project') and narrows the method to 'by domain' with a concrete example. It also explains that creation assigns an importance state, which differentiates it from sibling tools like set_competitor_importance.
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 use case is reasonably clear: add a competitor when you have a domain and want it tracked in a project. However, it does not explicitly mention alternatives such as set_competitor_importance for later changes, nor does it explain when not to use this tool.
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.