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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

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already indicate destructiveHint=true and idempotentHint=true. The description adds no new behavioral details beyond confirming deletion by key; no mention of side effects, error handling, or scope of deletion.

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 efficient sentences convey purpose, usage guidelines, and related tools. No fluff, every sentence adds value.

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

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple delete-by-key tool with good annotations and schema, the description covers the basics adequately. Could mention behavior if key does not exist, but overall sufficient.

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 parameter description 'Memory key to delete'. The description adds no additional semantics beyond what the schema provides, so baseline 3 applies.

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 uses specific verb 'Delete' and resource 'memory by key', clearly differentiating from siblings 'remember' and 'recall' by stating it is the deletion counterpart.

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: when context is stale, task done, or to clear sensitive data. Also names companion tools ('remember' and 'recall'), providing alternatives and 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

A3.8/5.0
Disambiguation3/5

Several tools form tight clusters that are easy to confuse: ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded are near-identical in routing, and the six polymarket_* tools (edges, arbitrage, edge_tracker, fill_risk, kalshi_spread, bet_research) all operate on prediction markets with overlapping names and purposes. While each has a distinct job, an agent will need to read descriptions very carefully to pick the right one, especially when many are similar.

Naming Consistency2/5

Naming conventions are mixed throughout the set: many tools use verb_noun (ask_pipeworx, compare_entities, discover_tools, resolve_entity, validate_claim), but there are also noun_noun (polymarket_edges, entity_profile, bet_research), adjective_noun (deep_research, recent_alerts), and bare verbs (forget, recall, remember, subscribe). No consistent pattern emerges, making tool names harder to predict and remember.

Tool Count2/5

At 34 tools, this server is heavy and tries to serve many unrelated domains—data research, prediction markets, package registries, memory, subscriptions, and AI visibility. The prediction-markets cluster alone accounts for six highly specialized tools that could be consolidated. The scope feels bloated rather than focused, which will overwhelm agents exploring the toolset.

Completeness4/5

Each domain within the server has solid coverage: data lookups offer stable, beta, grounded, and deep-research variants; entity analysis has profile, compare, changes, and resolve; subscriptions support create/list/delete/alert-read; memory has set/get/list/delete. Minor gaps exist (e.g., no direct package search by keyword, no tool to update a subscription), but the major workflows are covered and there are no dead ends.