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drmaxbdc

@drmaxbdc/productboard-mcp

by drmaxbdc

resolve_note

Resolve a Productboard note from UUID, numeric ID, URL, or deep link to get its v2 details. For numeric IDs, scans recent notes up to 500.

Instructions

Resolve a Productboard note from any identifier: UUID, numeric ID, web UI URL, or deep link. Returns the v2 note (with links.html — the web UI URL, equivalent to v1 displayUrl). For numeric IDs, scans up to 500 most-recent notes (~5 pages) matching against links.html. Includes archived notes in the scan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
identifierYesUUID, numeric ID (e.g. '54080737'), web UI URL, or deep link (?d=notes%2F...)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.1

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the return shape (v2 note with links.html, equivalent to v1 displayUrl), the fallback resolution algorithm for numeric IDs (scan up to 500 most-recent notes, ~5 pages), and that archived notes are included. It does not state failure behavior when a numeric ID is older than the scan window or any permission requirements, which keeps it short of a 5.

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?

Three dense sentences, front-loaded with purpose and accepted formats, followed by return shape and then the resolution caveat. Every clause carries information an agent needs; nothing is padding.

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 single-parameter read tool with no output schema, the description covers input formats, return contents, and the scan limitation, which is enough to invoke it correctly. It omits not-found/error behavior and any access requirement, but nothing critical is missing for correct invocation.

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 coverage is 100% for the single identifier parameter, so the baseline is 3. The description goes beyond the schema by tying parameter form to behavior: numeric IDs trigger a bounded page scan of up to 500 recent notes, which the schema does not say. That is genuine added meaning over the structured field.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (resolve) and resource (Productboard note) and immediately scopes the tool's differentiator: it accepts any identifier form (UUID, numeric ID, URL, deep link). This implicitly separates it from get_note/get_note_v1, which take a canonical ID, but no sibling is named explicitly, so the differentiation must be inferred.

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?

Usage is implied rather than stated: an agent can infer 'use this when you have a loose or unknown identifier' from the accepted-format list, and the numeric-ID scan note hints when the lookup is expensive. However, there is no explicit when-not-to-use guidance or named alternative such as get_note for known UUIDs, so routing requires inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.