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 declare destructiveHint=true and idempotentHint=true, so the core behavioral trait is covered. The description adds context about clearing sensitive data and pairing with remember/recall, but does not disclose additional unique behavior beyond what the annotations and schema imply.
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 the core action, and each sentence earns its place. No fluff 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?
For a simple one-parameter destructive tool with strong annotations and full schema coverage, the description provides enough context. It covers purpose, usage scenarios, and related tools, making it complete for its complexity.
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 schema covers 100% of the parameter with 'key: Memory key to delete', so the description adds no further meaning. The phrase 'by key' is redundant with the schema, yielding the baseline score.
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 'Delete a previously stored memory by key' with a specific verb and resource, and distinguishes itself from sibling tools like remember and recall by focusing on deletion. This clearly identifies the tool's unique purpose.
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 provides explicit use cases: 'Use when context is stale, the task is done, or you want to clear sensitive data' and suggests pairing with remember and recall. It lacks an explicit 'when not to use' clause, but offers strong contextual guidance.
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.
Each tool has a clearly distinct purpose with detailed descriptions that explain when to use which. Overlapping tools like ask_pipeworx vs ask_pipeworx_grounded are explicitly differentiated by use case (casual vs high-stakes). The Polymarket tools are highly specialized and non-overlapping.
All tool names follow a consistent snake_case pattern with descriptive terms (e.g., ask_pipeworx, resolve_entity, validate_claim). There is no mixing of camelCase or other conventions, making the names predictable and easy to parse.
With 33 tools, the count is above the typical 3-15 range, but it is justified by the server's broad scope covering multiple domains (SEC, FDA, FRED, prediction markets, etc.) and includes meta-tools for discovery and monitoring. Each tool seems necessary for the overall functionality.
The tool surface covers a comprehensive range of operations: data querying, entity profiles, comparisons, monitoring, memory, search, and even feedback. It includes both general-purpose and specialized tools, leaving no obvious gaps for the stated purpose of authoritative data retrieval and analysis.