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 description doesn't need to repeat that. It adds the use-case context about clearing sensitive data, but doesn't disclose additional behavioral traits like what happens if the key doesn't exist or whether deletion is reversible. This is adequate but not rich beyond what annotations provide.
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 two sentences, with the primary action front-loaded in the first sentence and usage guidance in the second. No wasted words; every phrase contributes to understanding the tool.
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 tool with one parameter, no output schema, and clear annotations, the description covers the essential context: purpose, when to use, and relationship to sibling tools. It omits error behavior, but that is not critical for a basic delete operation. Overall, it is sufficiently complete for the tool's simplicity.
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 100% for the 'key' parameter, and the description also references 'by key' but adds no extra meaning about formatting, constraints, or value semantics. The baseline 3 applies when the schema is sufficient, and this is the case here.
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: 'Delete a previously stored memory by key.' The verb 'Delete' plus the resource 'memory' makes the action explicit. It also distinguishes from siblings by contrasting with remember and recall, which store and retrieve memories.
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 the agent saved earlier.' It also references related tools ('Pair with remember and recall'), giving clear guidance on when this tool fits 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.
Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded differ only in mode; several Polymarket tools (polymarket_arbitrage, polymarket_edges, polymarket_fill_risk, bet_research) target related opportunities; ai_visibility_check and scan_competitor_ai_presence overlap. The meta-tools (discover_tools, suggest_questions, pipeworx_trending) could also be confused for one another.
All names are lowercase snake_case, which is consistent, but patterns vary: some are verb_noun (ask_pipeworx, resolve_entity, validate_claim), others are noun (news, crypto_prices, stock_metadata), and several use brand prefixes (pipeworx_*, polymarket_*). This mixed convention is readable but not predictable.
35 tools is too many for a coherent, well-scoped server. The set bundles a financial data API (Tiingo) with a generic data router (ask_pipeworx), prediction-market tools, memory utilities, subscription management, and npm checks — many unrelated to the server's apparent purpose, making it feel bloated.
For a Tiingo server, core data coverage is limited to stock prices, stock metadata, crypto prices, and news — missing real-time quotes, fundamentals, forex, technical indicators, and other typical Tiingo endpoints. Conversely, the general Pipeworx platform has broad query/research/subscription coverage but that domain doesn't align with the server name, leaving significant functional gaps.