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delete_ai_source

DestructiveIdempotent

Remove an AI source (its CSV + registration) by code so it is no longer applied on future imports. Set apply:true to re-import now. NOTE: the custom_ values already written onto products are NOT immediately erased — they clear on the next full product import. project_id is OPTIONAL (inferred for a single-project customer). Requires the additional-sources addon: without it the call is refused with error 'addon_required' (HTTP 403) + addonCode + upsellUrl — show the upsellUrl and do not retry. Returns {status:'deleted'|'not_found', code, applied}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
applyNo
project_idNo

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already carry destructiveHint=true and idempotentHint=true, but the description adds crucial context: custom_<code> values are not immediately erased but clear on the next full product import; the addon requirement (without it returns 403 with addonCode+upsellUrl, and instructs to show the upsellUrl and not retry); and the exact return shape. This significantly enriches the behavioral profile beyond annotations.

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 compact and front-loaded: the primary action and purpose appear in the first sentence. Supporting notes (delay, addon, return) follow logically without redundancy. Every sentence adds value; no filler or repetition.

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 destructive, idempotent mutation with an optional parameter and a prerequisite addon, the description covers all necessary aspects: what is deleted, when it takes effect, how to re-import, optional parameter behavior, the error condition and required response, and the return contract (including both statuses and the applied field). No critical information is missing.

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 0%, so the description must explain parameters. It does: code is the identifier ('by code'), apply is explained ('set apply:true to re-import now'), and project_id is noted as optional and inferred for single-project customers. All three parameters receive meaningful explanation, fully compensating for the schema gap.

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?

States the verb 'Remove' and the resource 'AI source (its CSV + registration)' and identifies the key 'code'. It clearly distinguishes this from delete_api_source or delete_feed by naming the resource type, so an agent can pick the correct deletion tool without opening the schema.

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?

The description clarifies the effect ('so it is no longer applied on future imports') and the option to re-import with apply:true. It does not explicitly name alternatives or state when to prefer this over delete_api_source, but the resource type is unambiguous. Context is clear; exclusions are not stated.

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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