Import an Instagram or TikTok post URL and run the AI virality analysis on it. COSTS 1 CREDIT from the user's plan (unless the post was already analyzed). Requires an active subscription. The analysis runs asynchronously: poll get_post_analysis with the returned post id until analysis_status is 'completed' (or 'failed').
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full post URL (instagram.com/reel/..., tiktok.com/@user/video/...) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond the annotations by disclosing that the operation costs 1 credit, requires an active subscription, and runs asynchronously with a required polling workflow. It also mentions the 'already analyzed' case that avoids a credit charge, which is valuable side-effect context that annotations do not provide.
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?
The description is compact and front-loaded: the core purpose appears first, followed by cost, subscription requirement, and the async polling behavior. Every sentence adds distinct, necessary information with no filler.
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?
For a one-parameter tool with no output schema, the description explains the essential workflow: what input to provide, the cost and subscription constraint, and how to consume the result by polling get_post_analysis with the returned post id. Nothing critical is missing for an agent to invoke and follow up 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?
The single parameter 'url' is already fully documented in the schema with examples of instagram.com/reel/... and tiktok.com/@user/video/...; the description adds no additional parameter-level semantics. With 100% schema description coverage, the baseline of 3 is appropriate.
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 states a specific action ('Import an Instagram or TikTok post URL and run the AI virality analysis') and clearly distinguishes the tool from siblings like get_post_analysis and get_post_preview by framing it as the initiating analysis step. The resource and behavior are unambiguous.
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 gives clear context on when to use the tool: when importing a post URL for virality analysis, requiring an active subscription, and noting the credit cost unless already analyzed. It names get_post_analysis as the follow-up for polling, but it does not explicitly state when to use alternatives like list_analyzed_posts to check existing analyses first.
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.
Each tool has a distinct target resource/action, and the descriptions are unusually explicit about differences (e.g., 'Distinct from the watchlist', 'Separate list from list_tags'). A few pairs are still easy to confuse without careful reading: delete_folder vs delete_folders differ only by singular/plural, and the three download-URL tools (get_post_download_url, get_asset_download_url, get_my_account_post_download_url) plus the category/tag families require attention to pick correctly.
The snake_case verb_noun pattern is followed consistently throughout (list_*, get_*, create_*, update_*, delete_*, set_*, tag_*). Minor deviations: archive_folder and archive_my_accounts also perform restore despite their names, delete_folder/delete_folders split one operation by cardinality, and tag_posts/tag_my_account use a different verb style than the set_* family for metadata mutations.
At 56 tools, this far exceeds the 25+ threshold for 'too many,' even though the server spans multiple subdomains (watchlist, analysis, assignments, folders, my accounts, assets, Drive, categories/tags). Obvious consolidation candidates exist — delete_folder/delete_folders, the three download-URL getters, and the parallel list_my_account_* listers — and the sheer surface is heavy for an agent to navigate.
Core workflows are thoroughly covered with no dead ends: watchlist → analyze → assign → folder → track → approve has full lifecycle support, including reversible archive vs permanent delete choices. Minor gaps exist but are work-aroundable: no create/update for my accounts or models (app-side OAuth/admin only), no way to delete a viral post or a post note, and asset upload only happens in the app.
