favorite_saved_assetToggle the favorite flag on a saved asset. Pass is_favorite=true to favorite, false to unfavorite. favorited_at is set/cleared in lockstep so the Favorites tab sorts correctly. Not destructive.
| Name | Required | Description | Default |
|---|---|---|---|
| asset_id | Yes | Asset to favorite or unfavorite. | |
| is_favorite | Yes | true to favorite, false to unfavorite. favorited_at is set/cleared in lockstep. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate idempotent and not destructive. The description adds context about favorited_at being set/cleared in lockstep for sorting correctness, enhancing transparency beyond annotations. No contradictions.
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 short sentences: purpose, usage, behavioral detail. No unnecessary words, easy to parse, and front-loaded with the core action.
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 description covers all necessary aspects for this simple tool: what it does, how to use parameters, behavioral effect, and safety (not destructive). Could mention error handling if asset doesn't exist, but that's a minor gap for a minimal tool.
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 coverage is 100% and both parameters have descriptions. The description adds value by specifying how to use is_favorite (true/false) and explaining the side effect on favorited_at, going beyond schema alone.
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 clearly states the tool toggles the favorite flag on a saved asset, using specific verbs ('Toggle', 'Pass'). It distinguishes from siblings like save_asset (which saves) and list_saved_assets (which lists) by explicitly mentioning the action and parameter usage.
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?
Explicitly tells when to use it (to favorite/unfavorite) and how to use the is_favorite parameter. However, it does not explicitly contrast with alternatives or state when not to use it, though the context is clear given siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.
Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.
112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.
The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.