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.
Input schema / examplesAdded value: +[
+ {
+ "key": "user_research_topic"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already disclose destructive and idempotent behavior. The description adds context that the tool acts on 'previously stored memory' by key and can be used to 'clear sensitive data,' which clarifies the operational effect beyond bare annotations. No contradiction with annotations.
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 three concise sentences: purpose, usage guidance, and companion tools. It is front-loaded with the core function and contains no unnecessary words 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 single-parameter destructive tool, the description fully covers purpose, usage, and pairing. Annotations handle safety/behavior, and no output schema is needed since it's a delete operation. The description is sufficient for an agent to decide when and how to invoke it.
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 already provides 100% coverage for the single parameter ('Memory key to delete'), so the description adds little semantic value beyond reinforcing 'by key.' Baseline of 3 is appropriate since the schema carries the parameter meaning.
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 tool's function with a specific verb and resource: 'Delete a previously stored memory by key.' It distinguishes itself from sibling tools like remember and recall by explicitly mentioning pairing with them, clarifying it is the deletion counterpart.
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 usage scenarios: 'Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier.' It also names companion tools (remember and recall), offering clear situational guidance relative to alternatives.
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 clearly distinct purposes, but some overlap exists: ask_pipeworx and ask_pipeworx_grounded are very similar (one grounded), and multiple Polymarket tools (arbitrage, edges, tracker, fill_risk, kalshi_spread) could be confused despite distinct roles. Overall, an agent can usually differentiate with careful reading.
Tool names follow mixed conventions: some use verb_noun (ask_pipeworx, compare_entities), others start with prefixes (pipeworx_, polymarket_, scan_), and a few are nouns (most_read, on_this_day). While readable, there is no consistent pattern, making it harder to predict tool names.
34 tools is high but not extreme for a broad-scope server. However, the server name 'wikifeed' suggests a Wikipedia focus, yet only 4 of 34 tools relate to Wikipedia (featured_article, most_read, on_this_day, picture_of_day). The tool count feels excessive relative to the name, but the actual breadth may justify it.
The toolset covers a wide range of domains (company data, prediction markets, factual queries, Wikipedia) with reasonable depth. Minor gaps exist: no Wikipedia search or edit tools, no direct tool for simple web search (relying on ask_pipeworx). Overall, agents can accomplish most tasks without hitting dead ends.