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imho.run game recommendations

Trending on Steam

trending
Read-onlyIdempotent

Steam games trending right now (imho.run/trending): rising = established games gaining reviews and players against their own recent baseline, breakouts = new games taking off. Each has reviews this week, growth in %, price, Steam Deck status and links. Use it for 'what's hot / popular right now on Steam'; for new releases use new_releases, for games like a given game use games_like. Games rated for adults only (explicit sexual content) are not covered; filtering is best effort.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
kindNorising
langNoLanguage of the `why` lines.en

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
langYes
sourceYes
statusYescollecting: the lists are not ready yet; results is empty.
resultsYes
page_urlYes
updated_atNo
attributionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add context — and it does, by enumerating the returned fields (reviews this week, growth %, price, Steam Deck status, links) and disclosing a coverage limitation: adult-only games are excluded and filtering is best effort. That caveat is real behavioral information an agent needs. It stops short of explaining ordering or result-count behavior, so not a 5.

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?

Dense but front-loaded: the core purpose comes first, then mode definitions, then the alternative routing, then the caveat. Every sentence carries weight, though the parenthetical URL and the field enumeration make it slightly list-heavy.

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?

An output schema exists, so return structure needn't be spelled out, yet the description still summarizes the payload. Combined with the enum semantics and the explicit sibling routing, an agent has what it needs to select and call this correctly; only ordering/pagination behavior is unaddressed.

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?

Schema coverage is only 33% (only `lang` is documented in the schema), so the description must compensate — and it does for the most important parameter by explaining what `rising` and `breakouts` actually mean, which the bare enum values do not convey. `n` and the return-count cap are left to the schema, which handles them adequately.

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?

States a specific verb+resource ('Steam games trending right now') and goes further by defining its two modes: `rising` as established games gaining against their own recent baseline, `breakouts` as new games taking off. An agent can distinguish this from new_releases and games_like without opening any schema.

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?

Gives an explicit trigger ('what's hot / popular right now on Steam') and names the alternatives with the condition that selects each: new_releases for new releases, games_like for games similar to a given one. This is exactly the when/when-not/alternatives structure.

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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