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facebook_profile_photos

Photo grid from a Facebook Page — full image URL plus accessibilityCaption (alt-text, not a post caption). Costs 2 credits. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFacebook profile/page URL, @handle, or page name. 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 20, max 200). The public /photos grid is a single SSR batch (often ~8) — retrievableCount is that batch, not a promise Facebook will fill limit. Flat 2 credits per call.

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses the 2-credit cost, that empty results and failures are never charged, the 24h cache behavior, and clarifies that accessibilityCaption is alt-text 'not a post caption'—a valuable disambiguation. It lacks only minor context such as rate limits or authentication needs, but the cost/cache/failure disclosures are strong for a public data-fetch tool.

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

Conciseness5/5

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

Four short sentences, each earning its place: purpose/output, cost, failure billing policy, and cache behavior. The core purpose is front-loaded first, and there is zero filler or repetition beyond what a standalone description legitimately needs.

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?

For a 3-parameter tool with 100% schema coverage and no annotations, the description covers the important operational facts: cost, non-charging of failures, cache semantics, and the key return field (accessibilityCaption). The absence of an output schema is a structural gap, but the description partially compensates by naming the return fields. Minor omissions like pagination behavior or error semantics are acceptable given the schema's rich limit parameter explanation.

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 all three parameters are already documented in the schema. The description's cache and credit mentions largely restate what the schema's cache and limit descriptions already say ('0 credits on hit', 'Flat 2 credits per call'). The accessibilityCaption note is output semantics rather than parameter meaning, so the description adds little beyond the schema baseline.

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—'Photo grid from a Facebook Page'—and specifies the output contents (image URL plus accessibilityCaption). It is easily distinguished from siblings like facebook_profile_posts, facebook_profile_reels, and facebook_details because it is the only photos-oriented Facebook tool. However, it lacks an explicit verb ('Retrieves'/'Fetches'), phrased as a noun phrase rather than a specific verb+resource construction.

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?

Usage context is implied by the unique 'photo grid' purpose, and operational guidance is given ('Pass cache=true for a free 24h cache hit'). However, it does not explicitly state when to prefer this tool over any Facebook sibling, nor name alternatives or exclusions. The schema's URL note adds cross-platform constraints, but the description itself provides no tool-selection routing among the large sibling set.

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.