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Get my taste

get_my_taste
Read-only

The signed-in reader's taste: the books, authors, series, genres and moods they love, what they avoid or quit, why each one counts, and how far from their usual taste they like to range. A recommendation for this reader rests on it, so it suits "what should I read next", "recommend me a book", "something I would like" and "what kind of books do I like" when no book or mood is named. The strongest 40 entries come back by default, and limit raises that. Needs a linked Siftivo account. It is the same profile the app's own recommendations use.

Input Schema

NameRequiredDescriptionDefault
limitNoMost steering entries to return, strongest first

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / limit
      Added value: +{
      +  "default": 40,
      +  "description": "Most steering entries to return, strongest first",
      +  "maximum": 500,
      +  "minimum": 1,
      +  "type": "integer"
      +}
  2. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare this a safe read (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the safety burden is off the description. It still adds real context: a linked Siftivo account is required, 40 entries return by default, and the data is the same profile the app's own recommendations use — the last point tells the agent the output is authoritative rather than a sample.

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?

Front-loaded with what the profile contains, then routing conditions, then operational notes. Three dense sentences with no filler, though the opening enumeration is long enough to be slightly heavy for a single-parameter read tool.

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?

There is no output schema, so the description must characterize the return — and it does, listing the entry types, the ranking (strongest first), the default size, and the reasons attached to each entry. Combined with the account-linking prerequisite, an agent has everything needed to call and interpret this tool.

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% and the single parameter is fully documented with default, min and max, so the schema does the heavy lifting. The description's "strongest 40 entries come back by default, and limit raises that" restates the schema default and ranking order without adding new syntax or format detail.

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 resource — the signed-in reader's taste profile — and enumerates its contents (books, authors, series, genres, moods, avoidances, reasons, range). It is clearly distinguishable from siblings like get_my_library or get_reading_index, which cover library holdings and reading activity rather than preference.

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?

Gives explicit trigger phrasings ("what should I read next", "recommend me a book", "something I would like") and an explicit exclusion: use it only "when no book or mood is named", which implicitly routes the agent to recommend_from_description or recommend_from_titles in the other case. That is genuine when/when-not routing.

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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