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vynly_search

Search users by @handle, tags by #topic, and posts by caption text. Use empty query to discover trending tags and featured users.

Instructions

Search Vynly across users (@handles), tags (#topics), and posts (full-text over captions). Use this to: (a) find an existing user before mentioning them, (b) discover what tags are active around a topic, (c) check if a hashtag has prior posts before using it, or (d) explore trending content with an empty query.

No authentication required. Returns three arrays: users (handle + verified + bio match), tags (name + post count), posts (id + caption + author + imageUrl). When q is empty or omitted, returns the current trending tags + featured users instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoSearch query. Plain text searches user bios, post captions, and tag names. Prefix with @ to restrict to user handles (e.g. '@oceanman'). Prefix with # to restrict to tag names (e.g. '#midjourney'). Omit or pass empty string to get trending topics instead of search results.
Behavior4/5

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

Discloses no authentication needed, describes return format (three arrays with fields), and specifies behavior when q is empty (trending/featured). Missing details on pagination or rate limits, but still strong given no annotations.

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?

Efficiently structured: purpose first, then bullet use cases, then return format. Every sentence adds unique value; no fluff.

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?

Covers search modes, use cases, and result structure. Could clarify whether @ prefix also matches bio fields (implies yes from return fields). Slight ambiguity but overall sufficient 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?

Single parameter 'q' already well-documented in schema with syntax examples. Description adds value by explaining empty query behavior and linking to use cases, but doesn't significantly extend schema info.

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?

Clearly states the tool searches across users, tags, and posts, with specific verb 'Search Vynly'. It differentiates from sibling tools (vynly_post_*, vynly_read_feed) by focusing on discovery and lookup.

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

Usage Guidelines4/5

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

Explicitly lists four use cases (find user, discover tags, check hashtag, explore trending) and notes no authentication required. Does not explicitly name sibling alternatives, but context makes distinction clear.

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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