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 destructiveHint=true; the description adds that it 'clears sensitive data', reinforcing the destructive nature. No contradictions. Could mention idempotent behavior but not required.
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 concise sentences: first defines the action, second provides usage guidance. No fluff; every sentence earns its place.
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 (single parameter, no output schema), the description covers all necessary information: action, usage context, and related tools.
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% and describes the 'key' parameter sufficiently. The description does not add additional semantic information beyond the schema, so baseline score of 3 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?
Clearly states 'Delete a previously stored memory by key', with a specific verb and resource. Distinguishes from sibling tools 'remember' and 'recall' by indicating deletion.
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?
Explicitly states when to use: when context is stale, task done, or to clear sensitive data. Also suggests pairing with 'remember' and 'recall', providing clear context for usage.
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 detailed usage guidance, but there are several overlapping entry points: ask_pipeworx, ask_pipeworx_beta (currently identical), ask_pipeworx_grounded, and deep_research; discover_tools vs suggest_questions; entity_profile vs recent_changes; and ai_visibility_check vs scan_competitor_ai_presence. The descriptions help, but the boundaries are not always crisp enough to prevent misselection.
Names are mostly lower_snake_case, but conventions vary widely: some are verb-first (list_subscriptions, resolve_entity), some are noun/adjective phrases (recent_changes, entity_profile), and several use brand prefixes (pipeworx_trending, polymarket_arbitrage). The naming is readable but lacks a single predictable pattern.
34 tools is well past the 25+ threshold and the scope sprawls beyond news/data into prediction-market arbitrage, npm dependency scanning, AI visibility audits, memory, subscriptions, and llms.txt generation. Each tool may be useful, but the set feels like several different servers merged into one, making it oversized and harder to navigate.
The research workflow is well covered: universal routing, grounded verification, deep research, entity resolution/profiles/comparisons, change feeds, discovery/onboarding, subscriptions, and memory all exist. Minor gaps include no direct pipeworx:// citation fetch tool and no broader account/profile management, but agents can work around these.