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Glama

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. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "key": "user_research_topic"
      +  }
      +]
  2. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Description aligns with annotations (destructiveHint=true, readOnlyHint=false) but adds no new behavioral details beyond stating 'delete'. Annotations already convey the destructive nature.

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 concise sentences with no waste. First sentence states action, second provides usage guidance. Front-loaded and efficient.

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 delete tool with one parameter and no output schema, the description covers purpose, usage context, and sibling relationships. Nothing missing.

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'. Tool description adds no extra meaning beyond what the schema provides, meeting the baseline.

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?

Description clearly states 'Delete a previously stored memory by key' with specific verb and resource, and distinguishes from siblings '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?

Explicitly provides scenarios for use (stale context, task done, clear sensitive data) and mentions pairing with related tools, but lacks explicit when-not to use.

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, but several overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (only differing in verification/depth), and polymarket_edges / polymarket_arbitrage / polymarket_edge_tracker / polymarket_fill_risk / polymarket_kalshi_spread all target similar prediction-market signals, which could cause mis-selection without careful reading.

Naming Consistency4/5

Most names follow a clear verb_noun pattern (resolve_entity, query_table, remember, recall, forget, subscribe, unsubscribe, validate_claim, compare_entities, search_within), but there are exceptions like ai_visibility_check (adjective_noun), generate_llms_txt (verb_noun with dot), and several polymarket_* names that are fine but inconsistent with the snake_case verb-first convention.

Tool Count5/5

35 tools is a large but reasonable surface for a broad data/serach platform covering company financials, economics, prediction markets, memory, subscriptions, and discovery. The count is justified by the wide domain, and the set is not bloated with trivial duplicates.

Completeness4/5

The surface covers core CRUD for entities (resolve, profile, compare, search, query) and memory (remember/recall/forget), plus subscriptions and meta-tools. Minor gaps: no explicit tool for updating/creating entities (understandable for a read-only data service), and no tool for listing all available table schemas beyond discovery (subjects covers this). Overall strong coverage.