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 already provide destructiveHint=true, so the description does not need to re-emphasize destructiveness. It adds useful context about why to delete, but no additional behavioral detail beyond 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?
Two sentences, front-loaded with purpose and followed by usage context. Every sentence adds value with no redundancy.
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 low-complexity tool with one parameter, full schema coverage, and clear annotations, the description is complete. It covers what, when, 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%, so description need not elaborate. The parameter 'key' is already described in the schema as 'Memory key to delete'; description adds no extra 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 uses a specific verb ('Delete') and resource ('memory') with a method ('by key'). It clearly distinguishes from sibling tools '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?
The description explicitly states when to use the tool ('when context is stale, the task is done, or you want to clear sensitive data') and mentions related tools for context.
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.
Many tools have distinct purposes (e.g., current_observations vs. climate_daily), but several query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, bet_research) overlap in function, all routing questions to a large tool catalog. This can confuse an agent about which to use.
Names are snake_case but follow no consistent pattern: some are verb_noun (ask_pipeworx), some noun_adjective (climate_daily), others compound (ai_visibility_check). The mix is readable but not predictable.
33 tools is high for a server named 'Weather Gc Ca', which implies a focused weather service. Many tools are unrelated to weather (Polymarket, SEC, FDA, etc.), making the count inflated and mismatched to the server's apparent scope.
For weather, the server covers alerts, current observations, and climate records but lacks forecasts, radar, satellite imagery, and station listings. While the broader Pipeworx catalog is extensive, the weather-specific surface is incomplete for a dedicated weather tool.