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Embers: Tabletop RPG Toolkit

Read a character's 5e24 level-up plan

vault_get_levelup_options
Read-onlyIdempotent

Read the level-up plan for a 5e24 character — the same computation vault's web wizard renders. Without classRuleId: the CHOOSER (the character's class entries with stored levels, the multiclass candidates each with warn-only prerequisite warnings[], xp.minimumForNext, atMaxLevel). A character with NO class entries (a hand-made sheet) gets RECORD mode instead: needsClassRecord: true plus recordOptions[] (every usable base class with subclasses[] and its subclassLevel) — record the existing classes with vault_record_pc_classes first, then re-read; the target plan and vault_level_up_pc reject a class-less character. With classRuleId: the TARGET PLAN for advancing that class one level — features[] (gained at the new level) / subclassFeatures[] / growth[] (held rules whose choice counts grew; their counts are DELTAS, "pick N more") each carrying its open choice blocks in the creation-option shape, plus multiclassGrants (entering a new class: fixed proficiency lines + skill/tool pickers), hitPoints {hitDie, average, conModifier}, prerequisiteWarnings[] (multiclass entry is warn-only, the player may proceed), spellSlots (combined multiclass pool preview when 2+ classes contribute), and xp {current, minimumForNewTotal}. Add subclassRuleId (at a subclass level, before committing the pick) to preview that candidate's features. ruleChoice pools arrive prerequisite-FILTERED — every listed option is one the character qualifies for at the level being gained. Read this before vault_level_up_pc and key every pick off what it returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
characterIdYes`_id` of the character to level (must belong to the calling user).
classRuleIdNoOmit for the CHOOSER (the character's class entries with their stored levels, the multiclass candidates with warn-only prerequisite warnings, the XP floor for the next level, atMaxLevel). Supply a base Class rule `_id` — one of the chooser's `classEntries[].classRuleId` to advance a held class, or a `multiclassOptions[]._id` to enter a new class at level 1 — for the TARGET PLAN: `features[]` / `subclassFeatures[]` / `growth[]` (each feature in the creation option shape with its open choice blocks: `choice` {label,count,options}, spellChoices (each block carries `prepared` — true = its spells land always-prepared and are EXCLUDED from the preparedSpellPicks pool), spellListChoices (same `prepared` flag), preparedSpells, proficiencyChoices, abilityScoreBump; `growth[]` entries are already-held rules whose counts grew this level — their `count`s are DELTAS, "pick N more"), `multiclassGrants` (when entering a new class), `hitPoints` {hitDie, average, conModifier}, `prerequisiteWarnings[]` (warn-only), `spellSlots` (the combined multiclass pool preview, null unless 2+ contributing casters), `openPickCount`, and `xp` {current, minimumForNewTotal}. ruleChoice pools arrive PREREQUISITE-FILTERED (an unqualified pick is also rejected on apply).
subclassRuleIdNoWith classRuleId, previews a tentative subclass pick before committing: the candidate's features (and their open choices) resolve into `subclassFeatures[]`. The pick itself still travels in `vault_level_up_pc.abilityChoices`, keyed by the class's subclass-choice ability.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description does not contradict them. Beyond that, it richly discloses behavior: RECORD mode for class-less characters, warn-only prerequisites, delta counts in growth[], prerequisite-filtered choice pools, null spellSlots when fewer than two casters contribute, and the fact that vault_level_up_pc rejects class-less characters. This goes well beyond what annotations or the schema alone convey.

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 description is long, but the length is justified by two modes, an edge case (no class entries), and important semantics like delta counts and prerequisite filtering. It is front-loaded with the core purpose and organized by mode. It loses a point because it partially restates details already present in the exhaustive schema, making it denser than strictly necessary.

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

Completeness5/5

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

Given the tool's complexity — three parameters, dynamic modes, sub-flows for class-less characters, and a rich output schema — the description is complete. It covers preconditions (record classes first), sequencing (read before vault_level_up_pc), postconditions (picks must come from returned options), and exceptional states (warn-only multiclass entry), so an agent has enough context to invoke it correctly in the broader level-up workflow.

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

Parameters5/5

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

Schema description coverage is 100%, so the baseline is 3, but the description adds mode-level meaning to each parameter: no classRuleId yields the CHOOSER, classRuleId selects a held class or a multiclass candidate for the TARGET PLAN, and subclassRuleId previews a tentative pick before commitment. It also explains the relationship between classRuleId values and the chooser output, which the schema alone does not make explicit.

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 states a precise action ('Read the level-up plan for a 5e24 character') and names the exact resource and computation it mirrors. It distinguishes the tool's two modes (CHOOSER vs TARGET PLAN) and calls out related siblings like vault_level_up_pc and vault_record_pc_classes, so an agent can tell it apart without opening schemas.

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

Usage Guidelines5/5

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

The description gives explicit usage conditions: omit classRuleId for the chooser, supply it for a target plan, and add subclassRuleId to preview a subclass pick. It also prescribes the workflow — read before vault_level_up_pc, record classes first when class-less, and key picks off the returned data — which is actionable routing guidance beyond the schema.

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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