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 indicate destructive and idempotent behavior. Description adds context about clearing sensitive data, which is beyond annotations. No contradictions.
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 states the core action, second provides usage guidance. No unnecessary words, well front-loaded.
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 full annotations, the description covers purpose, usage, and transparency completely. No gaps.
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 schema already describes the 'key' parameter well. Description does not add significant extra meaning beyond the 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?
Description clearly states 'Delete a previously stored memory by key,' specifying the verb and resource. It distinguishes from sibling tools like remember and recall.
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 says when to use: 'when context is stale, the task is done, or you want to clear sensitive data.' Provides alternatives: 'Pair with remember and recall.'
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 overlapping clusters: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions through the same 5,743-tool catalog, and ask_pipeworx_beta is currently an exact duplicate of ask_pipeworx. The Polymarket opportunity tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread, bet_research) also have fuzzy boundaries despite detailed descriptions.
There is no consistent naming pattern across the set: some tools are verb-first (ask_pipeworx, compare_entities, validate_claim), some are noun-first (entity_profile, recent_changes, polymarket_edges), and some are compound/multi-word oddities (temperature_random_generate, ai_visibility_check). Small internal clusters like remember/recall/forget and subscribe/unsubscribe/list_subscriptions show mini-consistency, but the overall convention is mixed and unpredictable.
With 32 tools, the server is over-stuffed, and many of them serve the same broad Pipeworx data/research purpose while one unrelated temperature tool rides along. The count is above the 25-tool threshold where a set starts to feel unwieldy, and several tools could be merged or dropped without losing real capability.
Assuming the intended scope is the Pipeworx data/agent platform implied by 31 of the 32 tools, coverage is strong: lookups, grounded verification, deep research, entity profiles, comparisons, entity resolution, claim validation, tool discovery, memory, subscription lifecycle, prediction-market analysis, execution risk, and feedback are all represented. The temperature_random_generate tool is a domain misfit rather than a completeness gap, and there are few obvious missing operations for the stated workflows.