forgetDelete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key to delete |
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 provide destructiveHint and idempotentHint. The description adds context about clearing sensitive data but doesn't elaborate on additional traits like persistence or confirmation behavior.
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, front-loaded with purpose, followed by usage guidance and sibling reference. No filler.
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 single-parameter destructive tool with annotations, the description adequately covers purpose, usage context, and relationships. No output schema exists, so no need to explain return values.
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 coverage is 100% and describes the 'key' parameter. The description only says 'by key', which adds no extra semantic value beyond 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 clearly states the action ('Delete') and the resource ('a previously stored memory by key'). It distinguishes sibling tools by pairing with 'remember' and 'recall'.
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?
Explicitly states when to use: 'when context is stale, the task is done, or you want to clear sensitive data'. Also mentions pairing with 'remember' and 'recall' for completeness.
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.
Several tools have overlapping functionality, especially in the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and the polymarket group (bet_research, polymarket_edges, etc.). Descriptions acknowledge these overlaps, making it difficult for an agent to choose the correct tool without deep understanding.
Naming conventions are inconsistent: some tools use snake_case (ask_pipeworx, bet_research), others use camelCase or PascalCase (ai_visibility_check, generate_llms_txt, polymarketArbitrage?). Also, tools like 'list_subjects' and 'get_data' have no clear pattern with the rest.
With 35 tools, the server feels overloaded and tries to cover too many distinct domains (data queries, prediction markets, subscriptions, memory, national statistics). This broad scope reduces coherence and makes the tool set harder to navigate.
The tool set covers a wide range of capabilities, from data retrieval to prediction market analysis and subscription management. However, the inclusion of Denmark-specific statistics tools (e.g., list_subjects, get_data) seems out of place and creates a niche gap for users interested in other national datasets.