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become-human

become-human

by 201Tech
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

forget

Remove a learned fact from the AI agent's memory by passing words that match exactly one stored fact, keeping user preferences and project knowledge accurate.

Instructions

Remove a learned fact. Pass words from it; it must match exactly one fact.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "fact": "<fact>"
    },
    "name": "forget"
  }
}

Input Schema

NameRequiredDescriptionDefault
factYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.3

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden for a destructive operation and it does not say whether removal is reversible, requires confirmation, or errors out on ambiguous matches. The only behavioral hint is the exact-one-match rule, which implies an ambiguity failure mode without describing it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

Two short sentences with the action first and the constraint second, no wasted words. It is arguably over-terse for a destructive tool rather than bloated.

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

Completeness2/5

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

A mutation tool with no annotations, no output schema, and no parameter descriptions in the schema needs the description to explain failure modes and irreversibility, and this one does not. An agent can attempt a call but cannot predict what happens when the match is ambiguous.

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 0% and the schema only says the parameter is a non-empty string, so the description must add meaning. It does partially: it tells the agent the string is words drawn from the fact (a fuzzy identifier), not an ID. It still leaves unanswered whether a substring, a paraphrase, or full wording is required.

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

Purpose4/5

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

"Remove a learned fact" gives a specific verb plus resource, which cleanly separates it from the read-only siblings (get_map, get_rules) and from map operations. It never names "remember" as the counterpart it undoes, so sibling differentiation is implied rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

The description supplies an invocation constraint (identify the fact by words from it, exactly one match) which is real usage guidance. It does not say when to use this versus remember, nor what to do when several facts match or none do, and it gives no prerequisites.

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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