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 indicate destructiveHint=true and idempotentHint=true. Description adds context about clearing sensitive data but does not significantly extend 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 no wasted words. Efficiently conveys purpose and usage.
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 all essential context and even references sibling tools for completeness.
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 single parameter 'key'. The description briefly mentions 'by key' but adds no new 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?
Clearly states 'Delete a previously stored memory by key' with a specific verb and resource, and distinguishes from siblings by mentioning '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?
Provides explicit when-to-use scenarios: stale context, task done, clear sensitive data. However, it lacks explicit alternatives or when-not-to-use guidance beyond referencing sibling tools.
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.
Several tools are deliberately near-identical variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) or have overlapping routing/query purposes (deep_research, validate_claim, discover_tools, suggest_questions). The Polymarket cluster also has five tools that all surface 'edges' or 'arbitrage' with only subtle differences. Only the three GeoNet tools and the memory trio are cleanly distinct.
The dominant style is snake_case, and clusters like ask_pipeworx_* and polymarket_* are internally consistent. However, verb/noun patterns vary widely across the set: some tools begin with verbs (get_quake, scan_dependency, generate_llms_txt), some are noun phrases (entity_profile, volcano_alerts, recent_changes), and some are plain nouns (polymarket_arbitrage). Readable but not a single predictable convention.
34 tools is well above the 'heavy' threshold, and the server is named 'Geonet Nz' while only 3 of its 34 tools relate to GeoNet. The overwhelming majority are Pipeworx/data/prediction-market tools, making the server's scope massively broader than its name implies. The count itself is not unreasonable for the actual feature sprawl, but it is inappropriate for the apparent purpose.
Taking the real scope as 'general authoritative data research + memory + subscriptions + a little GeoNet', the surface is quite complete: query entry points, grounded verification, deep research, entity resolution, comparisons, claim validation, monitoring subscriptions, memory persistence, and feedback are all present. The GeoNet-specific subset is also adequate (get one, list recent, volcano alerts). Minor gaps exist, like no general GeoNet station/well data or subscription editing, but nothing causes dead ends.