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Forget

forget
DestructiveIdempotent

Delete 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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key to delete

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide destructiveHint=true and idempotentHint=true. Description adds value by noting the operation deletes memory and explicitly states it clears sensitive data, offering behavioral context 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the action, and every sentence adds value with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

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 no output schema, the description covers purpose, usage context, and tool relationships completely.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already describes the 'key' parameter as 'Memory key to delete'. The description does not add extra meaning beyond what is in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Delete a previously stored memory by key' using a specific verb and resource. It 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.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly lists use cases: 'when context is stale, the task is done, or you want to clear sensitive data'. Also suggests pairing with related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tool families overlap heavily: ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded all route through the same 5,721 tools, polymarket_edges/polymarket_arbitrage/bet_research/polymarket_fill_risk all target prediction-market opportunities, and ai_visibility_check vs scan_competitor_ai_presence cover the same probe. An agent would struggle to pick the right one without reading every description carefully.

Naming Consistency3/5

There are coherent subfamilies (ask_pipeworx_*, polymarket_*, remember/recall/forget, list/read/fetch_feed), but the overall set mixes verb-first names (list_feeds, validate_claim, fetch_feed) with noun-first names (entity_profile, bet_research, deep_research) and adjective-led names (recent_alerts, recent_changes). The inconsistency is noticeable but not chaotic.

Tool Count2/5

34 tools is heavy for a server branded 'Law Feeds,' and many tools are off-domain (Polymarket betting, npm dependency scanning, AI visibility marketing, generic memory). The breadth could justify a larger catalog, but the overlapping research/Polymarket tools inflate the count beyond what the surface needs.

Completeness3/5

As a general data-gateway, the set is fairly complete: routing, grounded answers, deep research, entity resolution, comparison, subscriptions, memory, and feedback are all covered. Relative to the 'Law Feeds' identity, though, the surface is shallow — only list_feeds, read_feed, and fetch_feed serve that purpose, with no feed search, management, or update capabilities.