Pause a marketplace — synchronization to the channel stops until it is resumed with resume_marketplace. Returns {integrationId, action:'pause', status:'paused', kind}. marketplace_id is from list_marketplaces. project_id is OPTIONAL (inferred for a single-project customer; project_id_required otherwise — then call list_projects).
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | No | ||
| marketplace_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already carry readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the description only needs to add what pausing actually does. It provides that: synchronization stops until resumed, and the operation returns {integrationId, action:'pause', status:'paused', kind}. No statement contradicts the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
All four sentences are information-bearing: effect, return shape, marketplace_id source, and project_id rule. The most important behavior is front-loaded before the return and parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, the annotations cover safety and idempotence, and the description fills in the missing return shape and parameter provenance. Given no output schema, including the exact return object is valuable; nothing needed for correct invocation appears to be missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description carries the full burden and largely succeeds: marketplace_id is sourced from list_marketplaces, and project_id is explained as optional when inferred, otherwise requiring list_projects. It stops short of describing validation edge cases, but the semantics of both parameters are clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States the precise action ('Pause a marketplace') and the concrete behavioral effect ('synchronization to the channel stops'), while naming the inverse operation resume_marketplace. This clearly distinguishes it from siblings like pause_ad and pause_feed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says pausing persists 'until it is resumed with resume_marketplace', establishing when that related alternative is needed. It also gives acquisition guidance: marketplace_id is from list_marketplaces, and project_id handling depends on whether the customer is single-project, with list_projects as the fallback. It does not explicitly list exclusions for pause_ad/pause_feed, but the context is otherwise strong.
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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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.
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.
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.
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.
