Skip to main content
Glama
hinoyayoi

japanese-learning-memory

by hinoyayoi

upsert_item

Create or update a Japanese learning item by matching expression and item type, with support for readings, meanings, JLPT level, notes, and mastery scores.

Instructions

Create or update an exact normalized-expression and item-type match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNo
sourceNo
statusNolearning
readingNo
item_typeYes
expressionYes
jlpt_levelNounknown
meaning_jaNo
meaning_zhNo
usage_masteryNo
recall_masteryNo
speaking_masteryNo
listening_masteryNo
recognition_masteryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits, but it only states that it will create or update based on a match. It does not explain what happens when no match exists, whether multiple matches are possible, idempotency, or any side effects.

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 a single concise sentence with no filler. It is appropriately front-loaded, though its brevity borders on under-specification; however, that issue is more relevant to completeness than conciseness.

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

Completeness2/5

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

Given the tool's complexity (14 parameters, no annotations) and the presence of an output schema, the description is still too minimal. It lacks usage context, behavioral details, and parameter semantics, making it insufficient for an agent to reliably select and invoke the tool.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate, but it does not describe any parameters except indirectly implying 'expression' and 'item_type' as matching keys. The other 12 parameters remain unexplained, adding no meaning beyond the schema.

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 clearly states the action ('Create or update') and the matching criteria ('exact normalized-expression and item-type match'), which distinguishes it from sibling tools like search_items and add_relation. However, it does not explicitly name the resource ('item') though it is implied by the tool name.

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?

The description gives no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or context. The only usage signal is the name 'upsert_item' and the generic upsert behavior.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/hinoyayoi/japanese-learning-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server