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 indicate destructive and idempotent hints. Description adds usage context but no new behavioral traits beyond what 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?
Three sentences, front-loaded with action, no redundant information. Every sentence adds value.
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 tool's simplicity (one parameter, no output schema, clear annotations), the description fully covers purpose and usage contexts.
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 has 100% coverage for the single parameter 'key'. Description does not add additional semantic detail beyond 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?
Explicitly states 'Delete a previously stored memory by key', clearly identifying verb and resource. Pairs with related siblings remember and recall, distinguishing usage.
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?
Provides concrete when-to-use scenarios: stale context, task completion, sensitive data removal. Mentions pairing with siblings but does not explicitly state when not to use.
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 have distinct purposes, but there is some overlap between ask_pipeworx, ask_pipeworx_grounded, deep_research, and similar data query tools. However, detailed descriptions help agents differentiate.
Names consistently use snake_case and a mix of verb_noun and noun_verb patterns. No camelCase is present, but some tools like 'generate_llms_txt' have embedded acronyms, which slightly reduces consistency.
33 tools is high, but the server covers a wide range of functionalities (data lookups, prediction markets, RSS feeds, memory). Some tools could be combined, but the count is within reasonable limits for a comprehensive tool server.
The tool set covers major areas like entity lookups, prediction market analysis, data retrieval, and memory management. Minor gaps exist (e.g., no RSS feed deletion tool), but overall it is quite comprehensive.