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pinterest_board

Pins on a Pinterest board — saves, imageOriginal, destinationUrl, top-level author. ~0.5 credits/pin. Costs ~13 credits (0.5/result). Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPinterest board URL (.../username/board-name/), not a /pin/ URL. Example: https://www.pinterest.com/potterybarn/rustic-lodge-lookbook/. The URL platform must match this endpoint's platform. Do not pass cross-platform URLs, e.g. YouTube to TikTok, Instagram to Facebook, LinkedIn to X/Twitter, or Pinterest to Rumble.
cacheNoSet true to serve from the 24h response cache (0 credits on hit). Default false — always fetch fresh.
limitNoMax items to return (default 25, max 200). Billed per result.
cursorNoPagination cursor. Leave empty for the first page; then pass the nextCursor value returned in the previous response (numeric offset, e.g. 25). A null nextCursor means the end of the retrievable window (pidgets ~100).

TDQS

A3.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral disclosure burden and does so well: it discloses per-result credit cost, approximate total cost, that empty results and failures are not charged, and that cache=true provides a free 24-hour hit while the default is a fresh fetch. This goes beyond a simple read-only statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the resource and output fields. The only minor issue is redundancy around credit cost: '~0.5 credits/pin' and '~13 credits (0.5/result)' restate the same per-result pricing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the detailed input schema and no output schema, the description is mostly complete: it names the core returned fields, explains costs and cache behavior, and the schema handles pagination, limits, and URL constraints. A small gap is the lack of explicit sibling-tool routing, but an agent can still invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents url, cache, limit, and cursor in detail. The description reinforces the cache behavior and per-result billing, but it does not add significant parameter-level meaning beyond what the schema provides. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource as pins on a Pinterest board and names the key returned fields (saves, imageOriginal, destinationUrl, top-level author). It lacks an explicit verb like 'list' or 'fetch' and does not distinguish itself from sibling tools such as pinterest_user_pins, but the intent is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for Pinterest board scraping through its name and content, and the URL parameter schema reinforces what kind of URL is valid. However, it never explicitly states when to choose this tool over alternatives like pinterest_pin_details, pinterest_search, or pinterest_user_boards.

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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TDQS

B3.2/5.0
Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness4/5

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.