Run up to 100 record writes in ONE call (contact/company/deal/activity) - the fast path for imports/migrations. operations: [{object, method:create|update|delete, data|patch, id?}]. Returns a per-op result array (partial success). Every op still counts against your quota (batch saves round-trips, not quota).
| Name | Required | Description | Default |
|---|---|---|---|
| operations | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (destructive, not read-only, not idempotent), the description reveals that results are a per-op array allowing partial success, that every op counts against quota, and that batching saves round-trips. This is valuable behavioral context not present in the schema or annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences pack all essential info: limit, objects, operation shape, return format, partial success, and quota nuance. The most important fact ('up to 100 in ONE call') is front-loaded. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex batch tool with no output schema, the description adequately explains the operation format, return behavior (per-op result array), and critical constraints (quota, round-trips). It's sufficient for an agent to invoke correctly without additional documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'operations' has zero schema description coverage. The description compensates by explaining the exact shape: array of objects with fields object, method (create|update|delete), data|patch, and optional id. This adds meaning that the schema structure alone does not convey.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly names the verb 'Run' and the resource 'record writes' (contact/company/deal/activity), and specifies 'up to 100 in ONE call'. It stands apart from sibling single-record tools like relm_create, relm_update, and relm_delete due to its explicit batch nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides a clear use case: 'the fast path for imports/migrations', implying it's for bulk operations. It doesn't explicitly name alternatives or exclusions, but the context is strong enough to guide an agent when to choose this over individual write 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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Every tool targets a distinct resource-action pair (e.g., create_automation, create_pipeline, create_template), and potential overlaps like batch vs create or log_activity vs create are clearly differentiated in descriptions. No two tools appear to do the same thing.
All 41 tools follow the relm_<verb>_<noun> pattern in snake_case, with conventional verbs like create, get, list, delete, manage, and restore. Minor plural/singular differences (list_automations vs get_automation) follow standard resource-naming practices and do not break consistency.
At 41 tools, the set is far beyond the 25+ threshold and feels heavy for an agent to navigate. While the CRM domain is broad, many tools could be consolidated (e.g., generic get/list by resource type) without losing clarity.
The tool set covers the full record lifecycle (CRUD, restore, batch, search) plus schema management, pipelines, stages, automations, sequences, templates, webhooks, channels, and usage. However, automations, sequences, and templates lack update operations—requiring delete-and-recreate workarounds—which is a minor but notable gap.
