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Extract event metadata from a URL

floor10_extract_event_metadata
Read-only

Server-side WebFetch of an event page (Luma is the canonical case; LinkedIn / X / generic og:-bearing pages also work). Returns parsed { title, date, image, description, organization } so the agent doesn't have to scrape and parse OG / JSON-LD itself. Use the result to compose a HighlightStory. Args: { url }. Returns: a metadata map; empty fields where extraction missed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

TDQS

A4.9/5.0
Behavior5/5

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

The description discloses the tool makes a server-side web fetch (consistent with readOnlyHint=true), returns a map with empty fields on extraction failure, and specifies supported page types. This goes beyond annotations by detailing the behavior and error handling.

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?

The description is three sentences with no superfluous words. The first sentence immediately conveys the core action. It uses bullet-style listing in prose, making it clear and efficient.

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

Completeness5/5

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

Given the tool's simplicity (one parameter, no output schema), the description fully covers what the tool does, what it returns (including fields and empty handling), and supported page types. No other information is necessary for correct invocation.

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

Parameters4/5

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

The single parameter 'url' has no description in the input schema (0% coverage), but the description explicitly mentions 'Args: { url }' and clarifies what kinds of URLs are expected (event pages from Luma, LinkedIn, etc.). This adds meaning beyond the schema's format constraint, though it could specify URI format more explicitly.

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

Purpose5/5

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

The description clearly states it performs server-side WebFetch to extract event metadata from a URL, listing specific fields and canonical use cases (Luma, LinkedIn, X, generic OG pages). This specific verb+resource description distinguishes it from sibling tools like floor10_list_claimable_events or floor10_submit_highlight.

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

Usage Guidelines5/5

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

The description explicitly tells the agent to use the returned metadata to compose a HighlightStory, and notes that the tool saves the agent from manual scraping/parsing. This provides clear usage context, though it does not list alternative tools or when not to use, the context is sufficient for this simple tool.

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

A3.7/5.0
Disambiguation4/5

Most tools are clearly scoped to distinct actions (e.g., ic_hack_apply vs. ic_hack_register, ic_rooms_create vs. ic_rooms_join). A few pairs could confuse an agent: floor10_submit_highlight vs. floorcast_push both submit HighlightStories but to different queues, and ic_directory_search / ic_agent_directory_lookup / ic_admin_list_members overlap in searching members. Overall, the long descriptions help disambiguate, but the volume requires careful reading.

Naming Consistency3/5

The dominant pattern is ic_<domain>_<verb>_<object> (e.g., ic_admin_list_pending_events, ic_headsets_checkout), but there are notable deviations: floor10_* and floorcast_* prefixes break the ic_ convention, and a few tools use noun-style names (ic_health, ic_capabilities, ic_donations_total). Verb placement also varies (get_* vs *_get, e.g., ic_get_my_membership vs. ic_membership_set_profile). Still, most names are readable and predictable.

Tool Count1/5

175 tools is an extreme count for a single MCP server, far beyond the 50+ threshold that indicates an unwieldy surface. While the platform covers many domains (events, files, hackathon, headsets, prints, rooms, etc.), bundling everything into one server makes discovery and selection difficult. This would be better split into several narrowly-scoped servers.

Completeness4/5

The tool set covers nearly every lifecycle for each domain: CRUD for files/folders, full hackathon admissions and judging, headset lending with waivers and incidents, print farm submission and handoffs, and room coordination. Minor gaps exist: no delete for files/folders, no cancel for events, and some actions (like revoking a Z.ai key or tearing down a room) are explicitly left to human console use. Overall, the surface is remarkably comprehensive for the stated scope.