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get_full_apac_pack

Retrieve a full APAC compliance pack to fine-tune AI agents or provide complete context, with country briefs, outreach templates, etiquette guides, follow-up cadences, and stakeholder maps.

Instructions

Complete APAC pack for fine-tuning or full agent context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/main.ts:179-179 (registration)
    Tool 'get_full_apac_pack' is registered in the ListToolsRequestSchema handler with an empty input schema (no required arguments).
    { name: "get_full_apac_pack", description: "Complete APAC pack for fine-tuning or full agent context.", inputSchema: { type: "object", properties: {}, required: [] } }
  • Handler logic for 'get_full_apac_pack': returns all data modules (COUNTRY_BRIEFS, OUTREACH_TEMPLATES, ETIQUETTE_GUIDES, FOLLOWUP_CADENCES, STAKEHOLDER_MAP, COMPLIANCE_CHECKS) as a single JSON object.
    case "get_full_apac_pack": { return { content: [{ type: "text", text: JSON.stringify({ pack: "APAC Compliance MCP Complete v1.0", author: "Elisabeth Hitz", modules: { country_briefs: COUNTRY_BRIEFS, outreach_templates: OUTREACH_TEMPLATES, etiquette_guides: ETIQUETTE_GUIDES, followup_cadences: FOLLOWUP_CADENCES, stakeholder_map: STAKEHOLDER_MAP, compliance_checks: COMPLIANCE_CHECKS } }, null, 2) }] }; }
Behavior2/5

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

No annotations are present, and the description does not disclose behavioral traits such as whether the tool is read-only, the size of the response, or any side effects. The phrase 'for fine-tuning or full agent context' hints at a large output but is insufficient.

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

Conciseness2/5

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

The description is a single sentence, but it is too brief for a tool with no parameters and no output schema. It lacks detail on what the APAC pack contains, making it under-specified rather than concise.

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

Completeness1/5

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

Given the tool has no input schema, no output schema, and no annotations, the description must fully explain the return value. It fails to describe the contents or structure of the 'APAC pack,' leaving the agent without adequate information to use the tool effectively.

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?

The tool has zero parameters, and the schema coverage is 100%. The description does not need to add parameter meaning, so this dimension scores high. However, it could have clarified that no input is required.

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

Purpose3/5

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

The description specifies the tool returns an 'APAC pack' for fine-tuning or full agent context, which indicates a comprehensive data bundle. However, it lacks detail on the pack's contents, making it less specific than sibling tools like get_compliance_check or get_country_brief, which have clearer purposes.

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

Usage Guidelines2/5

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

No explicit guidance is provided on when to use this tool versus alternatives. The description does not differentiate use cases, such as when a full pack is preferred over individual packs like get_outreach_template.

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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