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Log events in bulk

bulk_log_events

Log finish or re-watch/re-read/re-listen events for many items in one call (max 250). Each entry takes media_type plus title or item_id, and optionally event_type, event_date (YYYY-MM-DD, YYYY-MM, or YYYY), rating, notes. An ambiguous title is skipped and reported, never guessed. Use for imports that carry finish dates.

Input Schema

NameRequiredDescriptionDefault
eventsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Adds real behavior beyond the annotations: ambiguous titles are skipped and reported rather than guessed, and there is a hard 250-entry ceiling. It does not state what a repeat call does (idempotentHint=false implies duplicates), nor how many entries succeed when some fail, which matters for a non-idempotent mutation.

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 tight sentences: what it does first, then entry shape and formats, then the safety behavior and intended use. No restatement of the title and no filler.

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?

For a one-parameter bulk mutation with no output schema, the description covers entry composition, date formats, item limit, partial-failure handling for ambiguous titles, and the intended scenario. An agent can construct a correct payload and predict failure modes from this alone.

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 description coverage is 0%, so the description carries the load and does it well: it enumerates media_type, title-or-item_id, and the optional event_type, event_date, rating, and notes, plus the accepted date formats (YYYY-MM-DD, YYYY-MM, YYYY). It omits any guidance on when to prefer item_id over title and on the rating scale.

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 and resource ('Log finish or re-watch/re-read/re-listen events') and immediately scopes it as bulk ('for many items in one call (max 250)'), which separates it cleanly from the single-item sibling log_event. The set of valid event kinds is spelled out, so an agent knows exactly what lands in the library.

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?

'Use for imports that carry finish dates' gives a concrete triggering scenario, and the 250-item cap signals when to split work. It stops short of explicitly naming log_event as the single-item alternative or saying what to do for the non-bulk case, leaving that inference to the agent.

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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