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by Longado
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Python
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set_rules

Record adopted or declined rule IDs from list_rules for a saved run; adopted rules are checked on every rerun.

Instructions

采纳或不要规则：adopted、declined 各写完整的规则 id 列表（id 来自 list_rules）。采纳的规则以后每次重跑都会检查。

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": {
      "saved_as": "<saved_as>",
      "adopted": "<adopted>"
    },
    "name": "set_rules"
  }
}

Input Schema

NameRequiredDescriptionDefault
adoptedYes采纳的规则 id，来自 list_rules；不采纳任何就写 []
declinedNo不要的规则 id，来自 list_rules
saved_asYes运行的保存名，来自 list_runs 或 build_ontology

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose one important trait: adopted rules are re-checked on every subsequent run. It does not say whether the call replaces prior adopted/declined state, is additive, or is reversible, which is a significant gap for a mutation tool.

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, front-loaded with the action and followed by the consequence. The opening phrasing is slightly terse, but every clause carries information.

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

Completeness3/5

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 no annotations and no output schema, the description covers input origin and one downstream effect but omits replacement semantics, what happens to unlisted rules, and the result of the 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%, and the description still adds meaning: both adopted and declined must contain the COMPLETE id list (not a delta), and ids must come from list_rules. That constraint is not evident from the schema alone.

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?

The description states a specific action on a specific resource: record which rules are adopted versus declined. The reference to list_rules as the id source anchors it against the sibling, though it never explicitly contrasts the two tools' roles.

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?

Usage is only implied: the agent must fetch ids from list_rules first, then call this tool to persist a decision. There is no explicit when-to-use/when-not-to-use statement or mention of alternatives such as skipping the call.

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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