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Read an automatic research rule

get_research_rule
Read-only

Reads a rule's limits, what it spent, which rows are waiting, and its recent runs.

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": "get_research_rule"
  }
}

Input Schema

NameRequiredDescriptionDefault
offsetNo
rule_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds real value by disclosing what the response contains (spend, waiting rows, recent runs) since no output schema exists, but it says nothing about pagination of those embedded lists, how far back "recent runs" goes, or cost of a large read.

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?

A single front-loaded sentence with no filler, and the most distinctive information (what the payload contains) arrives immediately. It is efficient, though its terseness is part of why parameter guidance is missing.

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 two-parameter read-only tool with no output schema and no annotations gaps, the description is adequate: it sketches the return shape and implies non-mutation. It falls short on the offset parameter and on how the embedded collections are bounded, which an agent needs to page correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must carry parameter meaning and it does not — rule_id and offset are never mentioned. rule_id is self-evident from its name, but offset (bounded 0–20000) is unexplained: an agent cannot tell whether it paginates waiting rows, recent runs, or something else.

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 pairs a specific verb ("Reads") with a specific resource ("a rule") and enumerates the payload sections: limits, spend, waiting rows, recent runs. This clearly separates it from list_research_rules (enumeration) and get_research_rule_results (result rows), though it does not name those siblings explicitly.

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: an agent can infer this is the way to inspect a single rule's status and cost exposure. There is no explicit statement of when to prefer it over get_research_rule_results or list_research_rules, and no prerequisites (e.g., rule must exist / have run) are given.

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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