mu_affiliateGet your personal MU affiliate (referral) link + stats. Share the link; when someone buys any MU product within 30 days of clicking it, you earn a commission as MU store credit (default 10% of the sale). You can also append the returned ref_param to any product URL. Returns clicks, sales (uses), earned_jpy and your mu_credit_balance. Requires Authorization: Bearer <api_key>.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does an excellent job: it explains the auth requirement ('Authorization: Bearer <api_key>'), commission details (10% within 30 days), return fields (clicks, sales, earned_jpy, mu_credit_balance), and usage of ref_param. No contradictions.
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 concise (approximately 70 words) and front-loaded with the primary purpose. Every sentence adds value: main function, benefit, usage, return fields, and auth. No redundant or vague phrasing.
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 simple parameterless getter with no output schema, the description is complete: it explains what the tool returns, how to use the results, and the auth requirement. No gaps remain given the low complexity.
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 input schema has zero parameters, so baseline is 4. The description adds no parameter information (none needed) but does not detract. It correctly notes the tool requires no arguments.
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 states the tool retrieves the user's personal MU affiliate link and stats, with a specific verb ('Get') and resource ('MU affiliate link'). It distinguishes from siblings by focusing on affiliate functionality, which is unique among the listed tools.
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 (when needing affiliate link/stats) but provides no explicit guidance on alternatives or when not to use. It lacks comparison with sibling tools, such as mu_check or mu_status, which might handle other retrieval needs.
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.
Each tool has a clearly distinct purpose; no two tools appear to do the same thing. Even closely related tools (e.g., mu_quote vs mu_rfq_create, mu_preview_mockup vs mu_create_product) are differentiated by read-only vs. action, or draft vs. send.
Tool names consistently use snake_case with the mu_ prefix, and follow a clear verb_noun or noun_verb pattern. Groups like mu_gi_*, mu_ship_*, mu_rfq_* maintain internal consistency. No arbitrary or ambiguous names.
The tool count of 28 is on the higher side but appropriate for the breadth of functionality (registration, product lifecycle, manufacturing, shipping, sales, admin). It's well within a manageable range for a comprehensive server.
The tool surface covers core workflows comprehensively: registration, product CRUD (with create, update, retire), manufacturing quotes (informational and RFQ with spec drafting), shipping (CSV, tracking, status updates), sales data, and gi-specific management. Minor gaps include lack of store update/delete and product search, but these are not critical for the main use cases.