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update_pantry_item

Update a pantry item's name, brand, category, unit, or notes while preserving stock and other data.

Instructions

Update an existing pantry item's metadata (rename, change unit, category, brand, notes). Internally fetches the current ArticleDto and PUTs back a merged copy — only the fields you pass change; everything else (current stock, price history, image URLs, autoRestock config) round-trips unchanged. Two API calls per invocation. Returns the updated ArticleDto. Use reduce_pantry_amount for stock changes — this tool only touches metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemIdYesItem uuid (from `list_pantry_items[].uuid`). Item must already exist.
nameNoNew name. Omit to keep current.
brandNoNew brand. Omit to keep current; pass null to clear an existing brand.
categoryUuidNoNew category uuid. Discover existing ones by inspecting `list_pantry_items[].categoryUuid`.
unitIdNoNew unit id, e.g. "pieces", "g", "ml". Changes how `amount` is displayed but does NOT convert existing stock.
notesNoFreeform notes. Omit to keep current; pass null to clear an existing note.
listIdNoList UUID — call `list_lists` to discover one. Optional only in stdio mode (falls back to the PANTRIST_LIST_ID env var); required explicitly in HTTP mode.
Behavior5/5

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

With no annotations, the description fully carries the burden. It discloses that the tool internally fetches the current `ArticleDto`, performs a PUT merge, makes two API calls per invocation, and returns the updated `ArticleDto`. This covers side effects, idempotency, and round-trip behavior comprehensively.

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?

The description is two tightly focused sentences. The first sentence defines purpose and scope; the second provides behavioral context, alternative tool, and expected return. Every word serves a purpose, no redundancy.

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 metadata update tool with 7 parameters, the description covers all needed context: what it does, when to use, behavioral details, and return type. No output schema exists, but the description mentions the returned `ArticleDto`. No gaps for effective agent invocation.

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?

All 7 parameters have schema descriptions (100% coverage), so baseline is 3. The description adds unique value by explaining the merge behavior and noting that listId is optional only in stdio mode, which enriches understanding beyond the schema.

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 clearly states the verb 'update', resource 'pantry item', and scope 'metadata' (rename, change unit, category, brand, notes). It also explicitly distinguishes from the sibling tool `reduce_pantry_amount` for stock changes, making its purpose unambiguous.

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 provides explicit guidance: 'Use `reduce_pantry_amount` for stock changes — this tool only touches metadata.' It also explains that only passed fields change, others round-trip unchanged, telling the agent when to use this versus alternatives.

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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