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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
Behavior5/5

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

The description states 'delete', aligning with annotations destructiveHint=true and readOnlyHint=false. It adds context about clearing sensitive data, enhancing transparency 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 concise with two sentences: the first states the core action, the second provides usage guidance. 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?

Given the tool's simplicity (one required parameter, no output schema) and comprehensive annotations, the description fully covers purpose, usage, and behavior. No gaps.

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 description does not add significant meaning beyond the schema's 'Memory key to delete'. Baseline 3 is appropriate as the schema already covers the parameter well.

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 explicitly states 'Delete a previously stored memory by key', which provides a clear verb and resource. It is distinct from sibling tools like '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 Guidelines4/5

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

The description gives specific situations for use: 'when context is stale, the task is done, or you want to clear sensitive data'. It also mentions pairing with related tools. Missing explicit when-not-to-use, but sufficient for context.

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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, especially the central data access tools like ask_pipeworx, deep_research, entity_profile, and compare_entities. However, the multiple polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) and the similar ask_pipeworx variants could cause confusion, especially for an agent quickly scanning options.

Naming Consistency4/5

Tool names are mostly snake_case and follow a verb_noun pattern (e.g., compare_entities, search_packs, resolve_entity). Some deviations exist, such as pipeworx_feedback, polymarket_arbitrage (starting with a noun), and single-word names like forget and remember, but overall the style is readable and consistent.

Tool Count2/5

With 36 tools, the server feels overly heavy. While the broad domain (structured data across many sources) justifies a large number, the count exceeds the recommended 15–25 range, making it unwieldy for agents to navigate efficiently without extensive discovery.

Completeness4/5

The tool set covers a wide range of domains: company financials, drugs, economics, prediction markets, weather, and even MCP discovery. There are few obvious gaps given the stated purpose, though some areas like social media or international data could be added. Overall, the surface is well-rounded.