Get the aggregated NMLP Knowledge Base (donor archetypes, routing tracks, condition grades, decision framework, donor glossary, named partners, coverage tiers).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only lists content categories. It does not disclose behavioral traits such as read-only nature, authentication needs, performance characteristics, or side effects.
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 sentence that is front-loaded with the action and lists contents. It is appropriately sized but slightly dense; could be split for better readability. 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?
Given the simplicity (no parameters, no output schema), the description provides adequate context by listing the knowledge base sections. It does not discuss return format or size, but for a simple read operation without parameters, it is largely complete.
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 is empty (0 parameters) and schema description coverage is 100%. The description adds value by enumerating the knowledge base contents, which compensates for the lack of parameters. Baseline for 0 params is 4.
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 'Get the aggregated NMLP Knowledge Base' (specific verb+resource) and lists included content areas (donor archetypes, routing tracks, etc.), which distinguishes it from sibling tools like nmlp_get_archive or nmlp_get_business_card.
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 this tool is for retrieving the knowledge base but does not explicitly state when to use it over alternatives or provide any contextual guidance. No exclusions or alternative tool names are mentioned.
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, from specific identifier lookups (CD, vinyl, LCCN) to donation logistics and first-edition identification. The general resolver (nmlp_resolve) is complementary and well-differentiated.
All tools follow a consistent pattern: 'nmlp_' prefix with descriptive snake_case names (e.g., nmlp_check_coverage, nmlp_identify_first_edition). There is no mixing of conventions.
At 16 tools, the count is slightly above the ideal 3-15 range, but each tool serves a non-trivial and distinct function across book identification, media lookup, and donation management, justifying the number.
The server covers core identification workflows (first editions, number lines, publisher rules, various identifiers) and donation operations, but lacks appraisal/pricing tools and more granular donation status tracking, which are minor gaps.