get_credit_transactionsCredit deductions + grants, newest first. Optional filters: type (e.g. EMAIL_SENT, LINKEDIN_INVITE, SDR_CONTACT), date range, pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | ISO date, e.g. 2026-06-30 | |
| from | No | ISO date, e.g. 2026-06-01 | |
| type | No | ||
| limit | No | ||
| offset | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It adds useful details: the result set is restricted to deductions and grants, and the ordering is newest-first. However, it doesn't describe the return record fields, default pagination behavior, or any edge-case behavior, leaving some important behavior implicit.
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?
The description is a single, dense sentence with no filler. The core behavior is front-loaded, and the optional filters are listed compactly without repeating schema details unnecessarily.
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 tool with five optional parameters and no output schema, the description covers the essential inputs and the ordering behavior. But it omits the response shape, default limits, and whether the date range is inclusive, so an agent must infer some conventions. It is adequate but not fully complete for a tool with no annotations or output schema.
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?
Schema description coverage is only 40%, but the description compensates by grouping the parameters into type, date range, and pagination, and by giving concrete type examples like EMAIL_SENT, LINKEDIN_INVITE, and SDR_CONTACT. This adds semantics beyond the schema's bare string type for the 'type' parameter and clarifies the purpose of the other parameters.
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 identifies the resource as credit transaction history, specifies the scope as 'deductions + grants,' and adds the 'newest first' ordering, which is specific enough to distinguish it from balance or aggregate usage endpoints among the credit-related siblings. It lacks an explicit verb, but the tool name supplies 'get,' so intent is clear.
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?
The intended use is implied by 'Credit deductions + grants' and the optional filters, but there is no explicit 'use when' or 'instead use' guidance. Given the many credit/usage siblings like get_balance, get_credit_usage_by_agent, and get_credit_usage_by_type, the description doesn't proactively route agents to the right tool.
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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Despite consistently detailed descriptions, several tool pairs have unclear boundaries: `get_subscription_limits` and `get_agent_plan_limits` describe essentially the same agent-slot check, `crm_get_conversation` and `crm_communication_thread` both claim to return the full message thread, and `get_credit_usage_by_agent` vs `get_credit_usage_for_agent` differ only by preposition. At 149 tools, an agent will regularly misselect between these near-duplicates.
The dominant pattern is verb_noun with domain prefixes (`crm_*`, `sdr_*`) and a consistent `preview_*` family that maps cleanly to destructive/expensive actions. Deviations are minor but real: CRM deletes use the inverted `delete_crm_*` form while other CRM ops use `crm_*`, and credit-usage tools mix `by_agent`/`for_agent` prepositions.
149 tools is nearly three times the 50+ threshold the rubric treats as extreme, even though the platform genuinely spans agents, campaigns, audiences, CRM, SDR, billing, and connections. Many could be consolidated without losing capability — e.g. the 11 balance/credit-usage tools, the two LinkedIn-account listers, and the 15+ preview variants.
The surface is remarkably complete: full CRUD/lifecycle coverage for agents, campaigns, audiences, CRM leads/stages, and SDR searches, plus billing, analytics, and connection management. Destructive or costly operations all have preview/approval counterparts, so there are no dead ends. If anything the risk is over-coverage rather than gaps.