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bobberrisford

affiliate-networks-mcp

affiliate_leaddyno_list_transactions

Retrieve affiliate transactions from LeadDyno with filters for status, date window, and programme to answer questions like 'what did I earn last month?' or 'show reversed sales'.

Instructions

List affiliate transactions (commissions earned, pending, reversed, or paid) on LeadDyno within a window or for a specific programme. Use this when the user asks "what did I earn last month?", "what's still pending?", or "show me reversed sales". Returns Transaction records including derived ageDays; pair with get_earnings_summary for aggregate totals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNo
fromNo
brandYes
limitNo
cursorNo
offsetNo
statusNo
maxAgeDaysNo
minAgeDaysNo
programmeIdNo
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool returns Transaction records including derived ageDays, and mentions scoping (window/programme). However, it doesn't explicitly state pagination behavior, authentication requirements, or that it's a read-only operation. The verb 'list' implies non-mutating, but richer disclosure would be better.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the action and scope, then gives usage examples, return information, and a pairing recommendation. Every sentence earns its place with no filler or redundancy.

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?

Given the tool's complexity (10 params, no annotations, no output schema), the description provides purpose, usage triggers, and return shape, but omits parameter semantics, pagination behavior, and an explicit list of valid status values. It is sufficient for tool selection but may not fully support autonomous invocation without inspecting the schema.

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?

The schema has 10 parameters with no descriptions (0% coverage). The description hints at 'within a window' (from/to), 'specific programme' (programmeId), and statuses (status), but it does not explain brand, limit, cursor, offset, minAgeDays, or maxAgeDays. For a 10-parameter tool, this is insufficient compensation for the low schema coverage.

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 uses a specific verb ('List'), names the resource ('affiliate transactions'), enumerates the statuses (earned, pending, reversed, paid), identifies the platform (LeadDyno), and states the scoping options (within a window or for a specific programme). This clearly differentiates it from sibling tools for other networks and from get_earnings_summary.

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 explicit usage triggers: "Use this when the user asks 'what did I earn last month?', 'what's still pending?', or 'show me reversed sales'". It also recommends pairing with get_earnings_summary for aggregate totals. It doesn't explicitly name exclusions among the many sibling list_transactions tools, but the network-specific name and triggers make the context clear.

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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