Day-by-day credit usage for spend monitoring (0 credits). Costs 0 credits. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Number of days to include (default 30, max 365). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully discloses zero cost, free failures/empty results, and cache behavior, but the claimed cache parameter does not exist in the schema. It also does not describe the shape of the returned daily usage data.
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 first sentence is front-loaded and clear, but 'Costs 0 credits' redundantly repeats the earlier '(0 credits)'. The invalid cache instruction adds confusion rather than value; two brief sentences still contain notable waste.
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?
This is a simple one-parameter tool with no output schema, and the description covers cost, caching, and failure policy. However, the invalid cache reference makes the instructions internally inconsistent, and it does not clarify what fields each daily usage entry contains.
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 schema documents 'days' well with default 30 and max 365, so the baseline is 3. However, the description invents a 'cache=true' parameter that the schema explicitly rejects via additionalProperties:false, creating harmful parameter confusion. It also adds no real meaning to the documented 'days' parameter.
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 opens with a specific verb+resource: 'Day-by-day credit usage for spend monitoring', which clearly distinguishes it from sibling tools like account_balance and account_request_history. The scope and free credit cost are immediately visible.
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?
It provides some context ('for spend monitoring') but no explicit when-to-use vs alternatives or exclusions. More importantly, it instructs 'Pass cache=true' even though the input schema only includes 'days' and additionalProperties is false, so this guidance is misleading and would fail validation.
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.
The platform-prefix convention keeps most of the 178 tools clearly separated, but several clusters are genuinely ambiguous: tiktok_live_info is explicitly described as 'Identical to TikTok Live', instagram_basic_profile and instagram_channel_details both return profile stats, and facebook_profile_posts overlaps with facebook_profile_reels. The generic 'Summarizer' descriptions for facebook_summarize, instagram_summarize, and tiktok_summarize provide no disambiguating detail at all.
The dominant snake_case platform_resource_suffix pattern is followed remarkably consistently across 178 tools (e.g. youtube_channel_videos, tiktok_search_users, reddit_subreddit_posts). Minor deviations exist: the same creator resource is called 'channel' in some tools (tiktok_channel_details, instagram_channel_posts) but 'profile' or 'user' in others (facebook_profile_posts, twitch_user_videos, linnkme_profile); link-in-bio tools mostly use _page but linkme uses _profile; and the video_summarize/video_transcript pair lacks a platform prefix.
At 178 tools this is far beyond what any agent can efficiently navigate in a single flat namespace, and even individual platform subsets exceed reasonable bounds (TikTok alone has ~34 tools, YouTube ~25). The sheer breadth of the multi-platform scope partially justifies the count, but the server would be far more usable split into per-platform servers.
The read-only data surface is impressively thorough: nearly every platform has profile + content + search + comments coverage, and TikTok, YouTube, Instagram, and Facebook are covered end-to-end including shops, ads, transcripts, and summaries. Notable gaps are minor: Twitter has no keyword search tool, LinkedIn lacks comments, and Reddit has no user-profile endpoint, but none of these create dead ends for the server's core data-retrieval purpose.
