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create_migration_test_plan

Generate a migration test plan covering 8 phases: pre-migration, data quality, transforms, sample migration, edge cases, rollback, performance, and post-validation with runnable Fix Scripts for user approval.

Instructions

Generate a full expert migration test plan for user approval before executing.

Covers all 8 testing phases:

  1. Pre-Migration Checks — table access, transform map active, ACLs, schema, correlation field, no duplicate IDs

  2. Source Data Quality — fill rates, null-heavy fields, long text truncation

  3. Transform Rules — value map completeness, null handling, date format conversion

  4. Sample Migration — end-to-end 1-record test, field accuracy spot-check, record count, zero import errors

  5. Edge Cases — special characters, duplicate source IDs, null reference fields

  6. Rollback Safety — clean delete by correlation field, no cascade side effects

  7. Performance — staging query speed, throughput estimate and runtime projection

  8. Post-Validation — zero error rows, correlation field populated, random spot-check

Each test case includes a ready-to-run ServiceNow Fix Script. Present the plan to the user for approval, then call run_approved_tests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
analysisYesThe full analysis object from analyze_migration_for_testing
field_mappingsNo
transform_rulesNo
sample_recordsNo
correlation_fieldNoSN target field that stores the source platform ID (used for dedup + rollback)u_source_id
source_id_fieldNoField in source records that is the unique ID (e.g. key for Jira, Id for Salesforce)Id
priorityNoall=full 8-phase suite | critical=blockers only | smoke=first 5 testsall
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It explains the tool generates a plan with test cases and does not execute anything (present for approval). However, it does not mention whether the plan is stored or how it is returned, leaving some behavioral ambiguity.

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?

The description is well-structured with a clear opening sentence followed by detailed bullet points of all 8 phases. It is somewhat verbose but each point serves to clarify the output. The main purpose is front-loaded, though the phase details could be more concise without losing clarity.

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

Completeness2/5

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

Given the tool's complexity (7 parameters, nested objects, no output schema), the description lacks explanation of how input parameters influence the generated plan. It thoroughly describes the output but omits the relationship between inputs and outputs, leaving the agent uncertain about parameter usage.

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 57%. The description does not elaborate on parameter meanings or usage beyond what the schema provides. Key parameters like 'analysis', 'field_mappings', and 'transform_rules' are not explained in context, so the description adds minimal value to parameter understanding.

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?

The description clearly states the verb 'generate' and the resource 'full expert migration test plan', with a specific audience and goal ('for user approval before executing'). It details the 8 testing phases, making it distinct from sibling tools like 'create_test_plan'.

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?

The description provides clear usage guidance: 'Present the plan to the user for approval, then call run_approved_tests'. This gives a workflow context. It does not explicitly exclude alternatives but the specificity of 'migration test plan' differentiates it from generic test plan tools.

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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