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Everloot: WoW Forever data

Profession leveling path

profession_path
Read-only

Leveling path for one Forever profession from Everloot uploads. A step exists only after 3 installs agree: on a reported recipe, or on the recipe colours that make it orange (a guaranteed skill-up), starting at the trainer's required rank. Gold exists only after 3 price uploads agree. No copied guide. Reads Everloot's current authorized public corpus when connected. Missing or unavailable data is reported explicitly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toSkillYesSkill to stop at. Must be above fromSkill.
fromSkillNoSkill the character has now.
professionYesProfession name, such as Alchemy.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
reasonNoWhy nothing was read, when connected is false.
dataAsOfYesThe corpus snapshot time, or null when unrecorded.
connectedYesFalse when no corpus was read; the page is then absent, which is not a measured zero.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior5/5

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

Despite annotations already covering the safety profile (readOnly, non-destructive), the description discloses substantive behavior the agent could not otherwise know: steps require 3 agreeing installs, gold requires 3 agreeing price uploads, no copied guides are used, the corpus is the currently authorized public one, and missing data is reported explicitly rather than silently omitted.

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?

The purpose is front-loaded in sentence one and the remaining sentences each carry new information. The consensus clause ('on a reported recipe, or on the recipe colours that make it orange...') is dense and slightly hard to parse, costing a point.

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?

An output schema exists, so return values need no explanation. The description covers sourcing, derivation rules and failure reporting; the only notable gap is the absence of guidance on when this tool is the right choice relative to its siblings.

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 description coverage is 100%, so profession, fromSkill and toSkill are already documented, including the constraint that toSkill must exceed fromSkill. The description adds nothing further about parameter meaning, so the baseline of 3 applies.

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?

States a specific verb and resource: it derives a leveling path for one profession, sourced from Everloot uploads, with an implied range (fromSkill to toSkill). The scope and data source are clear, but it never names or contrasts with the obvious siblings (everloot_plan, recipe_thresholds), leaving differentiation to inference.

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

Usage Guidelines2/5

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

There is no explicit statement of when to choose this tool over everloot_plan, recipe_thresholds, or search. Usage is only implied by the purpose, and no prerequisites or exclusions are given.

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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