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memo

memo

by ngabzar02
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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resolve_library_id

Resolve a library name into candidate IDs with trust scores and latest version, using an optional query to clarify ambiguous results.

Instructions

Resolve a library name (e.g. 'flask', 'nextjs') to candidate library IDs with trust scores and latest version. query is optional context to disambiguate.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "library_name": "<library_name>"
    },
    "name": "resolve_library_id"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNo
library_nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden and reveals the output includes 'candidate library IDs with trust scores and latest version', which goes beyond schema. It also notes that 'query' can disambiguate. It doesn't discuss side effects or error handling, but for a lookup-style tool this is reasonable behavior disclosure.

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?

A single, well-structured sentence conveys the core purpose and both parameters without padding. The examples are front-loaded and every clause adds value, making it easily scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the essential purpose, parameter roles, and high-level output (trust scores, latest version). With an output schema present and only two simple parameters, this is adequate. It lacks explicit guidance on when to use vs. siblings, but that is partially covered by purpose clarity, so a 4 is appropriate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It defines library_name with examples and explains query as optional disambiguating context. This adds meaningful semantics beyond the empty schema, though it could be more detailed (e.g., constraints on query).

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 'Resolve' and identifies the resource: library name to candidate library IDs. It also gives concrete examples ('flask', 'nextjs') and distinguishes from sibling tools by clearly stating the mapping from name to IDs, which get_docs and versions do not do.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by stating the tool resolves library names and mentions optional query context for disambiguation. However, it does not explicitly state when to prefer this tool over siblings like get_docs or versions, nor does it provide exclusion criteria or alternative guidance.

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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