Veezee: LinkedIn people & company data for agents

Get a Reddit user

reddit_get_user

Read-only

Fetch one Reddit user's public profile: username, account age, karma, follower count, and description. username is the name without the u/ prefix, e.g. 'spez'; a full profile URL also works. Add up to 2 sections from comments|posts|subreddits at 2 credits each: comments and posts return that user's recent activity (first page), subreddits returns where they are active. Costs 4 credits base. Use this to profile loud voices found via reddit_search before quoting or engaging them. To find users by topic, use reddit_search type=users; this tool needs an exact username.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`sections`	No	Extra activity sections, 2 credits each (max 2 per call).
`username`	Yes	Reddit username without the u/ prefix, e.g. 'spez'. Full profile URLs are accepted and cleaned.
`freshness`	No	recent (default) serves cached data from the last few hours when available; realtime forces a live fetch for +2 credits (refunded if we fall back to cached data). Trial keys are cached-only and reject realtime with TRIAL_CAP_EXCEEDED; paying upgrades this same key to unlock it.	recent
`max_credits`	No	Spend ceiling for this one call. The call is rejected (nothing charged) if its quote exceeds this. Only the quote is ever reserved, never this ceiling.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`usage`	Yes
`common`	Yes
`entity`	Yes
`platform`	Yes
`freshness`	Yes
`data_as_of`	Yes
`canonical_url`	Yes
`schema_version`	Yes
`platform_fields`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 10, 2026

TDQS

A5/5.0

Behavior5/5

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

Adds important behavioral details beyond annotations: base cost (4 credits), extra sections cost (2 credits each), freshness options (cached vs realtime), trial key limitations, and that activity sections return 'first page'. No contradictions with 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?

Description is concise yet complete, front-loaded with main purpose, then details. Each sentence serves a purpose with no redundancy.

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 4 parameters, 100% schema coverage, annotations, and an output schema, the description covers usage, cost, parameters, and alternatives comprehensively. No gaps.

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

Parameters5/5

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

With 100% schema coverage, the description still adds value: explains username format (without u/ prefix, full URL works), sections limit (max 2), freshness details (credits and fallback behavior), and clarifies that max_credits is a spending ceiling. All parameters are well-explained.

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 starts with 'Fetch one Reddit user's public profile' and lists specific data fields (username, account age, karma, etc.). It distinguishes from sibling tools like reddit_search and reddit_get_post, ensuring clear purpose.

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?

Explicitly states when to use: 'Use this to profile loud voices found via reddit_search before quoting or engaging them.' Also provides when-not guidance: 'To find users by topic, use reddit_search type=users; this tool needs an exact username.'

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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