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product_update

Destructive

Changes a product (only the passed fields) and returns its updated context; isArchived moves it to the archive with its versions, features and tasks, taking them out of work selection. Changes shared product structure; only at the user's request or with their consent.

Input Schema

NameRequiredDescriptionDefault
specNoNew product spec in Markdown (no HTML), in the language of the workspace data. Replaces the whole field: existing text, `::: doc` sections and `attach:`, `design:`, `color:` tokens stay only if included.
titleNoNew name
designNoProduct design files (Figma links); passed fields are replaced.
leadUIDNoNew product lead: employee UUID.
analyticNoNew product analyst: employee UUID or "any".
platformNoNew product platform.
productIDYesProduct ID
techStackNoNew technology stack; replaces the previous one.
isArchivedNotrue - archive the product, false - restore it.
isDeployEnabledNoWhether the product's tasks have a deployment stage.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=true, so the safety profile is covered; the description goes further by disclosing the archive cascade ('moves it to the archive with its versions, features and tasks, taking them out of work selection') and the partial-update behavior. It stops short of permissions, reversibility, or rate-limit detail, so it is strong but not exhaustive.

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 the core action, then the partial-update rule, then the archive side effect; no filler sentences. The archive sentence is dense but every clause carries new information.

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

Completeness4/5

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

For a 10-parameter destructive mutation with a fully documented schema but no output schema, the description covers scope, consent, and the most dangerous side effect. The return value is only gestured at ('returns its updated context'), which is the one remaining gap.

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 coverage is 100%, so baseline is 3, but the description adds a meaningful global rule the schema does not state per-field: only explicitly passed fields are changed. That materially affects how an agent treats the nine optional parameters.

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?

States a specific verb and resource ('Changes a product') and adds the partial-update scope ('only the passed fields') plus the return ('its updated context'). It is clearly distinguishable from read-only siblings like product_context or product_list, though it does not name any sibling explicitly.

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?

Provides an explicit precondition: 'only at the user's request or with their consent,' which tells the agent when this mutation is permitted. It does not, however, point to alternatives (e.g., product_context for reads) or state when not to use it beyond the consent rule.

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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