Resume a paused marketplace — synchronization to the channel starts again. Returns {integrationId, action:'resume', status:'resumed', 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?
Beyond the annotations (readOnly=false, idempotentHint=true, destructiveHint=false), the description adds the actual return shape and the conditional project_id behavior. It explains what resuming does functionally. It does not cover edge cases like already-resumed marketplaces, but the idempotent hint partially covers that.
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?
Three sentences with no wasted words. The purpose is front-loaded, the return value is given compactly, and the parameter guidance is packed into the final sentence without repetition.
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?
Even without an output schema, the description provides the return shape, parameter provenance, and the conditional project_id logic. For a simple resume operation with idempotent and non-destructive annotations, nothing essential is missing for an agent to call it correctly.
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?
Schema description coverage is 0%, so the description carries the full burden, and it succeeds. It tells the agent that marketplace_id comes from list_marketplaces, and explains exactly when project_id is required versus inferred, including the fallback call to list_projects.
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?
The description uses a specific verb-resource pair ('Resume a paused marketplace') and states the concrete outcome: 'synchronization to the channel starts again.' It is clearly distinguished from sibling tools like resume_ad and pause_marketplace by naming the marketplace resource.
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 context is clear: use it for a paused marketplace that needs synchronization resumed. It also gives workflow guidance for the optional project_id ('inferred for a single-project customer; project_id_required otherwise — then call list_projects'). However, it does not explicitly contrast this with alternative resume tools or state when not to use it.
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.
