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lurq

Version-exact runtime surface

resolve_surface
Read-only

What a package version ACTUALLY exports at runtime, extracted from its shipped JavaScript rather than from documentation or the model's memory: names and arity, not type signatures (use usage for those). Call before writing code against a package whose API may have moved. Runtime existence is what decides whether an import throws; a removed type breaks tsc, a removed runtime symbol breaks the program. A miss returns UNKNOWN and queues extraction, UNKNOWN never means the symbol is absent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesnpm package name
versionNoExact version; omit for the latest extracted

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Adds substantial context beyond annotations: the extraction source (shipped JavaScript vs. documentation/memory), the distinguishing concern (runtime existence vs. type existence affecting tsc vs. program), and importantly the miss behavior ('A miss returns UNKNOWN and queues extraction, UNKNOWN never means the symbol is absent'). Annotations only cover read-only/open-world; the description supplies the semantic behavior an agent needs to interpret results correctly.

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

Conciseness4/5

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

Three dense sentences, front-loaded with what the tool returns and immediately followed by the alternative-tool distinction and the call-timing recommendation. Every sentence carries informational weight, though the runtime-vs-type explanation is slightly elaborate.

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?

For a read-only extraction tool with a small 2-param schema and no output schema, the description covers purpose, source of truth, sibling routing, and result semantics (UNKNOWN handling). No output schema means the description's note about names/arity and UNKNOWN is valuable, though return shape is only partially implied.

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

Parameters3/5

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

Schema coverage is 100%, with both parameters fully described ('npm package name', 'Exact version; omit for the latest extracted'). The description adds no parameter syntax or format beyond what the schema provides, so the baseline 3 is appropriate.

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?

States a specific verb+resource combination — what a package version actually exports at runtime, extracted from shipped JavaScript. It explicitly distinguishes itself from the sibling tool 'usage' ('names and arity, not type signatures (use usage for those)'), so an agent can route correctly without opening both schemas.

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?

Provides clear context for when to use it — 'Call before writing code against a package whose API may have moved' — and names the alternative ('usage') for type signatures. No explicit when-not-to-use beyond the usage distinction, but the routing condition is concrete.

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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