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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate destructiveHint=true and idempotentHint=true. Description confirms deletion and adds context about clearing sensitive data. No contradictions, but could mention irreversibility or security implications.
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 with zero waste: purpose first, then usage guidance. Perfectly front-loaded and efficient.
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 and no output schema, the description, combined with annotations, covers purpose, usage, safety, and idempotency. No gaps identified.
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% with the 'key' parameter described as 'Memory key to delete'. Description adds no additional meaning beyond the schema, so baseline score is appropriate.
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?
Description clearly states 'Delete a previously stored memory by key' with specific verb, resource, and method. It distinguishes from sibling tools like 'remember' and 'recall' by implying deletion versus creation or retrieval.
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 explicit use cases: 'Use when context is stale, the task is done, or you want to clear sensitive data.' It also suggests pairing with related tools, though it lacks explicit 'do not use' 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.
There are several clusters of tools with overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all do data-fetching/research with somewhat subtle differences. Polymarket tools also overlap (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, bet_research, polymarket_kalshi_spread). However, most tools have detailed descriptions that clarify their distinct roles, and the core data-lookup tools are differentiated by grounding level and scope.
Most tools follow a consistent verb_noun or noun_verb pattern (e.g., search_registrants, list_foreign_principals, get_registrant_documents, subscribe, unsubscribe, remember, recall, forget, resolve_entity, validate_claim). Deviations include brand-name tools like ask_pipeworx, pipeworx_feedback, pipeworx_trending, and polymarket_kalshi_spread that mix conventions but are still readable and predictable within their domain.
34 tools is heavy for a single MCP server, especially with multiple overlapping research entry points (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, suggest_questions). The broad data-router nature of the server explains the size, but it is still a large surface that would be better consolidated.
The server covers its visible domains well: data lookup, grounded verification, entity profiling, comparison, change tracking, subscription lifecycle, memory, and FARA-specific queries. Minor gaps exist (e.g., no direct tool for updating saved memory beyond forgetting/re-remembering, no tool to create custom alert types beyond the three supported categories), but the core workflows are complete.