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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

A4.3/5.0
Behavior3/5

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

Annotations already provide destructiveHint: true and idempotentHint: true. The description adds minimal extra behavioral context beyond the rationale of clearing sensitive data, but does not discuss irreversibility, missing keys, or side effects. This is adequate but not enhanced beyond the 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?

Two sentences, front-loaded with the core action and followed by usage scenarios. No filler or redundant content; every word earns its place.

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?

Given a simple one-parameter tool, full schema coverage, no output schema, and strong annotations, the description covers all necessary information for an agent to select and invoke the tool correctly.

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% with the 'key' parameter fully described as 'Memory key to delete'. The description merely restates 'by key' without adding further semantic detail, so it does not add value beyond 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 starts with a specific verb and resource: 'Delete a previously stored memory by key.' This clearly distinguishes it from sibling tools like remember and recall, and the action is unambiguous.

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 states when to use: 'Use when context is stale, the task is done, or you want to clear sensitive data.' Also mentions pairing with remember and recall, providing clear guidance on relationships with alternatives.

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

B3.1/5.0
Disambiguation1/5

The tool set includes multiple pairs of nearly identical tools (e.g., ask_pipeworx and ask_pipeworx_grounded, bet_research and polymarket_arbitrage) that overlap heavily in purpose. Many tools also combine unrelated functions, making it difficult for an agent to select the right one without confusion.

Naming Consistency1/5

Tool names follow no discernible pattern: snake_case (ai_visibility_check), verb_noun (ask_pipeworx, get_bill), and even lengthy descriptive names (scan_competitor_ai_presence) are mixed. The naming style is chaotic and inconsistent across the set.

Tool Count2/5

With 30 tools, the count is excessive for a server supposedly focused on OpenStates (state legislatures). Only a few tools (search_bills, get_bill, etc.) relate to the server's name, while the rest are tangentially related to data lookups, betting, or AI visibility, making the set bloated.

Completeness1/5

The server's core domain (state legislative data) is severely underserved: only about 5 tools cover bills and legislators, lacking basic CRUD operations like create, update, or delete. Many obvious operations (e.g., searching bills by subject, tracking votes) are missing, while unrelated tools dominate.