mcp-server

update_rule

Idempotent

Update an EXISTING product rule (Attribute Rule). ALWAYS validate_rule the new document first and fix every error. Identify the rule by rule_id (from list_rules / get_rule) and pass the full rule document as rule — {name, description, category, icon, rules:[{sortId, enabled, type, conditions, operationGroups: [{mode, parentMode, attributes, operations:[{name, arguments:{key:value}}]}]}]}. The safe pattern is: get_rule, edit the returned document, validate_rule, then update_rule with it. Only name, description, category, icon and rules are editable; usage/bookkeeping fields are preserved server-side. A get_rule document already carries map_attribute_value search/replace in the correct {value:''}-objects form (paired by index) — edit those entries verbatim, never flatten them to plain strings (plain strings save but map nothing). update_rule keeps ruleId + every attachment, so the edit updates all attributes using this rule; the value/options mapping is not run by validate_rule's dry-run — verify after a real export/build. scope selects the library: 'project' (default) or 'shared_template' (a template_read_only error means your access cannot write there). Returns {ruleId, scope, status, changed, reason, validation}; status 'updated' / 'no_changes' on success, or 'rejected' with the validation errors when invalid (HTTP 200, nothing written). SAVE-ONLY: the edit reaches a feed's output only after export_feed on the feeds that use this rule. project_id is OPTIONAL (inferred for a single-project customer; project_id_required otherwise — then call list_projects).

Input Schema

TableJSON Schema

Name	Required	Description
`rule`	Yes
`scope`	No	Which library the rule lives in: 'project' (default) = the project's own library; 'shared_template' = the reusable shared template library.
`rule_id`	Yes
`project_id`	No

TDQS

A5/5.0

Behavior5/5

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

Annotations only state readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds substantial behavioral context: server-side preservation of bookkeeping fields, ruleId and attachments are kept, map_attribute_value objects must remain verbatim, validate_rule's dry-run does not execute value/options mapping, and updates only reach feed output after export_feed. It also discloses HTTP 200 behavior on rejected validation with nothing written.

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 long but every sentence carries necessary operational detail for a complex mutation with no output schema. It front-loads the core purpose and critical validation rule, then systematically covers identification, document structure, editable fields, return statuses, and post-update export requirements. There is 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?

Given the complex nested rule parameter, no output schema, and the nuanced relationship with validate_rule and export_feed, the description is complete. It covers required inputs, optional inputs, scoping, validation behavior, return contract, authentication-relevant scope errors, and downstream effects. An agent has enough information to call this tool correctly.

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

Parameters5/5

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

Schema description coverage is only 25% (only scope has a description). The description compensates fully: it explains rule_id identification, provides the complete nested rule document shape, clarifies scope values and the template_read_only failure mode, and explains project_id optionality with single-project inference versus project_id_required.

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 opens with 'Update an EXISTING product rule (Attribute Rule)', which states a specific verb, resource, and scope. It clearly differentiates from sibling tools like create_rule and delete_rule by emphasizing 'EXISTING' and describing the full update workflow.

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 explicitly prescribes the safe pattern: get_rule, edit the returned document, validate_rule, then update_rule. It also names where to get rule_id (list_rules / get_rule) and explains when scope selects 'project' vs 'shared_template'. It also addresses edge conditions like template_read_only errors and project_id_required.

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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TDQS

A4.2/5.0

Disambiguation4/5

Tools are organized around distinct resources (ads, marketplaces, feeds, orders, rules, sources) with clear action verbs, and descriptions explicitly disambiguate near-pairs like get_feed_status vs ad_status or set_feed_filter vs set_feed_attribute_filter. A few similarly named status/action pairs (e.g. ad_status vs get_ad, run_ad_item_action vs run_ad_operation) require careful reading, but overall the purposes are separable.

Naming Consistency4/5

The overwhelming majority follow a consistent verb_noun snake_case pattern (list_*, get_*, create_*, set_*, run_*, test_*). Minor deviations like ad_status and marketplace_status (noun-based status tools) and koongo_knowledge break the pattern slightly, but the convention is clearly recognizable and predictable.

Tool Count1/5

At 105 tools, the surface is extreme and far beyond the 50+ threshold, even for a complex e-commerce integration domain. Much of the bloat comes from systematic triplication across ads, marketplaces, and feeds (e.g. three nearly identical map_*_attribute tools, three list_*_items, three get_*_report) that a generic resource parameter could have consolidated.

Completeness4/5

The toolset covers the full lifecycle of feeds, ads, marketplaces, order connections, rules, and imports, including create/read/update/delete, status monitoring, item-level actions, validation, repair, and restore. Minor gaps exist, such as no delete for standalone order connections and limited update capabilities for some entities, but these are workable and do not create dead ends for the core workflows.

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