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by com.leapmemory
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Update a rule

update_rule
Idempotent

Change the wording or scope of a rule the user already saved. Use this when they correct or narrow an existing rule, rather than calling add_rule again, which would leave both versions in force. Call list_rules first to get the rule_id; never guess one. Pass only the fields that change.

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": {
      "rule_id": "<rule_id>"
    },
    "name": "update_rule"
  }
}

Input Schema

NameRequiredDescriptionDefault
textNoThe new wording. Omit to leave it unchanged.
scopeNoThe new scope: 'always', or a project or activity name. Omit to leave it unchanged.
rule_idYesThe id of the rule to change, from `list_rules`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the safety profile is covered; the description adds the non-obvious consequence that re-creating instead of updating leaves duplicate rules in force. It does not describe behavior on an invalid rule_id or any authorization requirements, leaving a small gap.

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?

Four short sentences, front-loaded with purpose before the routing guidance and the prerequisite. Every sentence carries distinct information: purpose, alternative, prerequisite, and patch semantics.

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 three-parameter mutation tool with full schema coverage and annotations covering safety and idempotency, the description supplies all the decision-relevant context. No output schema exists, but the description does not mention what is returned (e.g., the updated rule), which is a minor omission for a state-changing call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so all three parameters are already fully documented, establishing a baseline of 3. The description adds intent beyond the schema by framing the call as a partial patch ("Pass only the fields that change"), reinforcing the omit-to-leave-unchanged contract at the call level rather than the field level.

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?

States a specific verb and resource ("Change the wording or scope of a rule") and immediately scopes it to rules the user already saved, which separates it from creation-oriented siblings. An agent can distinguish it from add_rule without opening either schema.

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?

Gives explicit when-to-use ("when they correct or narrow an existing rule"), an explicit when-not-to-use with the concrete consequence (calling add_rule again "would leave both versions in force"), and a prerequisite workflow ("Call list_rules first... never guess one"). Nothing is left to inference.

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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