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Browse the best-practices library

get_best_practices
Read-only

Browse OTP's best practices library -- 1,500+ actionable rules from 9 publishers (Google, AWS, Deloitte, Accenture, etc.). Search by keyword, filter by category or publisher. Each practice is a prescriptive rule with why and failure mode. Requires API key.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_best_practices"
  }
}

Input Schema

NameRequiredDescriptionDefault
qNoSearch query (e.g. 'prompt engineering', 'data governance', 'agent coordination')
pageNoPage number (default 1)
limitNoResults per page (default 50, max 200)
categoryNoFilter by category (e.g. 'Machine Learning', 'MLOps', 'AI Strategy', 'Prompt Engineering', 'AI Governance')
publisherNoFilter by publisher profile ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered; the description still adds auth requirements ('Requires API key') and discloses the shape of each result ('a prescriptive rule with why and failure mode'). That is real context beyond the structured fields, though it says nothing about pagination defaults or total-result limits.

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?

Three compact sentences with the scale and content detail front-loaded and no filler. The opening 'Browse OTP's best practices library' slightly restates the title, costing a bit of density.

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?

With no output schema, the description carries the burden of describing return values and does so qualitatively (prescriptive rule + why + failure mode). Combined with the auth note and corpus size, an agent has enough to call it correctly; only pagination/result-count behavior is unaddressed.

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 description coverage is 100% and all five parameters are documented with examples in the schema itself. The description restates the same three filter axes (keyword, category, publisher) without adding format or syntax detail, so the baseline 3 applies.

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?

States a specific verb and resource ('Browse OTP's best practices library') and quantifies the corpus (1,500+ rules, 9 publishers), which makes it clearly distinguishable from the adjacent get_publishers / get_my_rules / export_rules_markdown siblings. It doesn't explicitly name a sibling to contrast with, so it stops short of a 5.

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?

'Search by keyword, filter by category or publisher' tells the agent how to drive the tool, and 'Requires API key' implies a prerequisite. However, there is no explicit when-to-use vs. when-not guidance and no routing to nearby tools like get_publishers for enumerating publishers before filtering.

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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