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 go beyond what annotations imply.
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?
Description is two sentences with clear front-loading of the primary action. No unnecessary words.
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 low complexity, description covers purpose, usage, and pairing. Missing mention of idempotency or return value, but annotations cover the former.
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 already covers the only parameter 'key' with a description. Description merely restates 'by key', adding 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?
Description clearly states the verb 'Delete' and resource 'memory by key'. It also distinguishes from siblings by mentioning pairing with '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 states when to use (context stale, task done, clear sensitive data) and suggests pairing with alternatives (remember, recall). Lacks explicit 'when not to use' but is still very clear.
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 have unclear boundaries: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, and deep_research, validate_claim, discover_tools, and suggest_questions all overlap with the ask_pipeworx family. The prediction-market cluster also has six tools whose distinctions require careful reading, making mis-selection likely.
Most names are lowercase snake_case and reasonably descriptive, but no consistent verb_noun pattern holds across the set. entity_profile, recent_alerts, and pipeworx_trending are noun phrases, while compare_entities, resolve_entity, and validate_imei are verbs, and the useful ask_pipeworx_* and polymarket_* prefixes are not applied server-wide.
33 tools is too many for an agent to navigate efficiently, especially since the underlying data surface is already hidden behind ask_pipeworx and dozens more tools. The set spans data research, prediction markets, memory, subscriptions, IMEI validation, dependency scanning, and llms.txt generation, making it feel like a grab bag rather than a focused server.
The main query/verify/research/monitor workflow is covered well: ask, grounded, deep research, claim validation, entity profiles, comparisons, subscriptions, and memory all exist, so common paths have few dead ends. However, the set is not a single coherent domain, and there is no direct fetch/read-record tool or prediction-market execution tool, leaving some reasonable follow-up actions implicit.