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mcp-server

by com.koongo

delete_rule

DestructiveIdempotent

Delete a product rule (Attribute Rule) and unlink it from every feed attribute that uses it. DESTRUCTIVE: a rule may shape a live feed — check its usageCount with list_rules / get_rule first, warn the user, then call with confirm:true. Without confirm:true the call returns error 'confirm_required' and nothing is deleted. Identify the rule by rule_id (from list_rules). scope selects the library: 'project' (default) or 'shared_template' (a template_read_only error means your access cannot write there). Returns {ruleId, scope, status:'deleted', changed, reason, validation}. Any feed that used this rule reverts to its other value source; run export_feed on those feeds to refresh their output. project_id is OPTIONAL (inferred for a single-project customer; project_id_required otherwise — then call list_projects).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNoWhich library the rule lives in: 'project' (default) = the project's own library; 'shared_template' = the reusable shared template library.
confirmNoMust be true to actually delete; without it the call returns 'confirm_required' and nothing is deleted.
rule_idYes
project_idNo

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations that already mark destructiveHint=true, the description discloses the confirm_required guardrail, the unlink behavior, the effect on feeds reverting to another value source, and the return payload shape. It also explains that export_feed should be run on affected feeds, which is important operational context.

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 dense but well-structured, front-loading the destructive nature and key prerequisite before scope and project_id details. Every sentence carries real guidance, though the information density makes it slightly longer than strictly necessary.

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?

The description covers prerequisites, error cases, return values, side effects, and required follow-up actions. With no output schema present, it fully explains what the agent should expect and do, leaving no critical gaps for a destructive operation.

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 coverage is only 50%; rule_id and project_id lack descriptions in the schema. The description compensates by explaining how to identify the rule via list_rules and by detailing when project_id is optional versus required, adding meaning the schema alone does not provide.

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 states a specific verb and resource — 'Delete a product rule (Attribute Rule)' — and clearly distinguishes the scope of what happens: the rule is deleted and unlinked from every feed attribute using it. It differentiates from siblings like update_rule by naming the unique destructive behavior and its consequences.

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 gives explicit when-to-use guidance: check usageCount with list_rules/get_rule first, warn the user, and only call with confirm:true. It also explains the shared_template access error and how to handle missing project_id, providing clear prerequisites and troubleshooting steps.

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.

Resources