Destructive — removes a user_rule. Only call when the user explicitly asks to delete or remove a rule.
| Name | Required | Description | Default |
|---|---|---|---|
| rule_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| ok | No | ||
| error | No | ||
| message | No | ||
| upgrade_url | No |
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?
Annotations already mark the tool as destructive and not read-only. The description reinforces this and adds an important behavioral guardrail: explicit user consent is required before calling. It does not detail side effects, but the annotations plus this condition provide adequate transparency.
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 the destructive warning front-loaded. There is no filler, and every sentence 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 one-parameter destructive tool with an output schema and rich annotations, the description covers purpose, risk, and invocation conditions well. The only minor gap is guidance on sourcing rule_id, but the surrounding sibling tools like list_user_rules make this a small omission.
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 0%, and the description says nothing about rule_id beyond the tool name. The agent must infer that rule_id is the identifier of the user_rule and how to obtain it, which is a notable gap for the only required parameter.
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 the exact operation: 'removes a user_rule'. It clearly distinguishes this from sibling tools like add_user_rule, update_user_rule, and list_user_rules, and the verb is specific and unambiguous.
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 gives an explicit invocation condition: 'Only call when the user explicitly asks to delete or remove a rule.' This clearly implies not to call it for other intents, though it does not name alternative tools such as update_user_rule.
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 map cleanly to distinct resource+action pairs: projects, tasks, skills, user rules, memory, and messaging are all clearly separated. The main ambiguity is update_task versus update_task_state, since update_task can also change state and plan_status, though the descriptions do point to the narrow intended use.
The naming is largely consistent verb_noun snake_case: create_project, update_skill, delete_task, list_projects, get_context, save_turn. Minor deviations include recent_messages lacking a verb, remove_user_rule versus delete_* style, and singular user_rule in mutations versus plural user_rules in listing.
With 27 tools, the server is over the typical well-scoped MCP range, even though it covers several domains. Some consolidation is possible, such as folding update_task_state into update_task and reducing the overlapping retrieval/search tools.
The tool set provides strong lifecycle coverage for projects, tasks, skills, and user rules, plus memory retrieval, agent messaging, and onboarding help. Minor gaps exist, like no standalone get_task or list_tasks and no explicit inbox listing, but get_project and get_context largely cover those needs.
