Get credit spend by connection for an agent
get_credit_usage_for_agent_connectionsPer-channel credit spend (widget, telegram, phone, etc.) for one agent. Identifies the costliest channels.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes |
get_credit_usage_for_agent_connectionsPer-channel credit spend (widget, telegram, phone, etc.) for one agent. Identifies the costliest channels.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the returned data type ('per-channel credit spend') but does not state read-only behavior, time period covered, result ordering, authentication needs, or what happens when agent_id is invalid. This is a notable gap for an unannotated tool.
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 short sentences with no filler. The first sentence states the core behavior and the second adds decision-relevant value by explaining the tool identifies the costliest channels. Every sentence earns its place.
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?
Adequate for a simple single-parameter read operation, but it lacks a time period (e.g., monthly, all-time) and does not describe the output shape despite there being no output schema. Among many credit-related sibling tools, the exact distinction could be sharper, though the core purpose is understandable.
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 agent_id parameter has zero schema description, but the description says the data is 'for one agent,' which clarifies that agent_id identifies the agent whose channel spend should be returned. With only one obvious parameter, this modest context is sufficient compensation for the 0% schema coverage.
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 states a specific verb-resource pair ('credit spend by connection') and clearly scopes it to 'Per-channel credit spend ... for one agent.' The concrete examples (widget, telegram, phone) and the 'per-channel' framing distinguish it from sibling tools like get_credit_usage_for_agent or get_credit_usage_by_type, even without naming them.
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 description implies when to use the tool: when you need per-channel credit spend and want to identify costliest channels. However, it does not explicitly state when not to use it or name alternative sibling tools, so an agent has to infer the selection logic from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.