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analyze_dependencies

Analyze dependencies for data migration from Jira or Salesforce. Scans users, detects parent-child relationships, and proposes a sequenced migration plan.

Instructions

Phase 3: Analyse migration dependencies before building artifacts.

For Jira: - Scans all referenced users (assignee/reporter), checks if they exist in ServiceNow - Identifies issue type hierarchy (Epic/Story → Task/Bug → Subtask) - Proposes a sequenced migration plan (Tier 1 = parents first, Tier 2 = children, etc.)

For Salesforce: - Counts records per object - Detects parent/child object relationships (e.g. Account → Contact, Account → Case) - Checks record owners (OwnerId) against ServiceNow sys_user - Warns if a parent object is not included in the migration scope - Proposes migration order (parent objects first, child objects after)

Always call this after discover_schema and before build_artifacts. If users are missing, ask the user whether to auto-create them in SN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformYesSource platform (salesforce, jira, or any registered connector)
project_keysYesJira project keys or Salesforce object names to analyse (e.g. ["EMAL","KAN"] or ["Account","Contact","Case"])
auto_create_usersNoCreate missing SN users automatically
Behavior5/5

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

No annotations provided, so description bears full burden. It thoroughly explains behavior for Jira (user checks, hierarchy, sequenced plan) and Salesforce (record counts, relationships, owner checks, warnings, order). No contradictions.

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?

Well-structured with Jira and Salesforce sections plus usage note. All sentences add value; no redundancy. Front-loaded with primary purpose.

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?

No output schema, but description hints at outputs (plan, counts, warnings). Covers preconditions and behavior. Could be more explicit about return value format, but adequate given complexity.

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 covers all 3 parameters with descriptions (100% coverage). Description repeats basic parameter meaning but does not add significant additional context beyond schema. Baseline 3 appropriate.

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?

Description clearly states the verb 'analyse', resource 'migration dependencies', and phase 'Phase 3'. It distinguishes from siblings by specifying its place in the workflow (after discover_schema, before build_artifacts) and provides platform-specific detail.

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

Usage Guidelines4/5

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

Explicitly instructs to call after discover_schema and before build_artifacts. Advises on handling missing users. Lacks explicit alternatives or when-not-to-use, but context is clear given sibling tool names.

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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