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crm-lifecycle-ops

crm-lifecycle-ops

What breaks if I change this

what_breaks
Read-only

Identify what depends on an attribute, segment, list, content block, event, message, or text in Braze, Klaviyo, or Iterable before changes, with live items first and source evidence.

Instructions

Everything that depends on an attribute, segment/list, content block, event, message or piece of text, live items first, each with how we know (api-verified, parsed from template, seen on screen…) and a list of live items we can't rule out.

Input Schema

NameRequiredDescriptionDefault
kindYes
valueYesName or id, e.g. loyalty_tier, VIP members, footer_v2, Order Placed, or a phrase/URL.
platformYesWhich platform.
workspaceNoWorkspace label. Defaults to the connected one, or "demo" when nothing is connected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine value by disclosing result ordering ('live items first'), the provenance markers per item ('api-verified, parsed from template, seen on screen'), and a separate bucket of 'live items we can't rule out' — information not available in annotations and important given there is no output schema.

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

Conciseness3/5

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

It is a single run-on sentence with no separation between what the tool returns, how results are ordered, and the caveat list. It is short, but the clauses are not front-loaded and the lack of structure makes it harder to scan than its length warrants.

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?

Because there is no output schema, the description usefully sketches the return shape and ordering. However, it omits routing guidance relative to closely related siblings and says nothing about scope limits (e.g., cross-platform behavior, what 'live' means), leaving meaningful gaps for an impact-analysis tool.

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 coverage is 75% and the schema already supplies enum values plus examples ('loyalty_tier, VIP members, footer_v2, Order Placed, or a phrase/URL'). The description's enumeration of kinds largely restates the schema's kind enum and adds no format or matching semantics beyond it.

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 makes clear this is a dependency/impact analysis: it returns 'everything that depends on an attribute, segment/list, content block, event, message or piece of text.' The verb is implicit (the tool name carries it), but the resource and scope are specific enough to distinguish it from siblings like list_items or find_overlaps.

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?

There is no statement of when to use this versus alternatives such as find_overlaps, list_items, check_campaign, or what_changed, and no preconditions (e.g., must be connected, what happens in demo mode). The agent must infer usage from the purpose sentence alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.