remove_account
Stop tracking an account. Free.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| account_id | Yes | Account UUID |
Stop tracking an account. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| account_id | Yes | Account UUID |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Free' but does not explain side effects such as whether tracking history is deleted, whether the action is reversible, or any permission requirements.
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 very concise, consisting of two short statements. 'Stop tracking an account' is essential, and 'Free' adds some value but is not crucial. No unnecessary length or repetition.
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 simple nature of the tool (one parameter, no output schema), the description covers the core action. However, it lacks information about the consequences of the operation, such as what happens to account data or whether the action is idempotent, which would be helpful 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 already documents account_id as 'Account UUID' with 100% coverage. The description adds no additional meaning about the parameter, so the baseline score of 3 applies.
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 action 'Stop tracking an account' with a specific verb and resource. It distinguishes itself from sibling tools like 'untrack_video' by focusing on accounts, and contrasts with 'track_account'.
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?
No guidance is provided on when to use this tool versus alternatives. The description does not mention any prerequisites, scenarios, or exclusions, leaving the agent without explicit direction.
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 targets a distinct resource and action: account vs video vs folder vs analysis vs radar. Even similar tools like analyze_video and get_analysis are clearly separated by creation vs retrieval.
Most names follow a verb_noun pattern (track_video, get_account, create_folder). Minor deviations like 'growth_trends' and 'radar_history' are noun phrases but remain readable and predictable.
26 tools is slightly above the ideal range, but the server covers a broad domain with distinct sub-areas (accounts, videos, folders, analytics, AI analysis, radar), so the count is justified rather than bloated.
Core lifecycle operations are covered: track/untrack accounts and videos, list/get details, analytics, folders, and AI analysis. Minor gaps exist (no delete folder, no remove-from-folder), but they don't break primary workflows.