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news_feed_search_ugc

Read-onlyIdempotent

[Read] Reddit/Discord/Telegram/YouTube-style UGC: non-empty query uses vector API; coin without query uses OpenSearch. Both empty invalid. X/Twitter narrative -> search_x; headlines -> search_news. Not macro economic statistics; not structured event list -> get_latest_events. Read-only public research data. No account access, no order placement or fund transfers. Not investment advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinNoTicker filter; with query filters results; without query required with index for OpenSearch list mode.
limitNoMax items; default 10, max 50.
queryNoOptional NL query; non-empty uses vector search. May combine with coin; both empty is invalid.
domainNoUGC topical bucket: crypto / defi / finance / macro / ai_agent / web3_dev / all (default all). macro = social discussion about macro themes, not CPI/Fed/unemployment statistics (use macro data tools) or get_latest_events.
channelNoOptional source channel e.g. r/ethereum or handle.
sort_byNorelevance (default) / upvotes / recent.
platformNoreddit / discord / telegram / youtube / all (default all).
time_rangeNo1h / 24h / 7d (default) / 30d / all.
quality_tierNoA (default, high quality) / B / all.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinNo
countYes
itemsYes
limitNo
queryNo
totalYes
domainNo
channelNo
sort_byNo
platformNo
time_rangeNo
duration_msYes
quality_tierNo

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already claim readOnlyHint=true and destructiveHint=false, and the description reinforces this with 'Read-only public research data. No account access, no order placement or fund transfers.' It adds the dual-API behavior (vector vs OpenSearch) and the 'Not investment advice' disclaimer beyond what annotations provide. Effortless consistency with annotations, adding context rather than repeating them.

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?

A single dense paragraph, but every sentence earns its place: operation type, modes, routing rules, exclusions, and safety notes. It's front-loaded with the [Read] tag and purpose. Slightly heavy as one block, but information density-to-length ratio is high and there is zero filler.

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?

With an output schema present, return values need no explanation. The description covers the core operational modes, exclusions, sibling routing, and safety posture. For a 9-parameter tool with a rich schema, this is reasonably complete; the only minor gap is that it doesn't spell out behavior when query is empty with no coin, but the schema notes 'both empty is invalid'.

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 the schema carries the burden of documenting all 9 parameters. The description complements by explaining the query/coin interaction modes but doesn't detail individual parameter syntax; that's left to a fully-covered schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 (search) and resource (UGC: Reddit/Discord/Telegram/YouTube-style). It distinguishes itself from siblings explicitly: 'X/Twitter narrative -> search_x; headlines -> search_news', making the boundary clear without needing to open other schemas. The [Read] prefix reinforces the operation type.

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?

Exceptionally explicit. It describes the two operational modes ('non-empty query uses vector API; coin without query uses OpenSearch'), states invalid states ('Both empty invalid'), and gives routing guidance to alternatives ('search_x', 'search_news', 'get_latest_events'). No ambiguity about when or when not to use this 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

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource or action: event lists vs details, news index vs open web vs X vs multi-platform UGC, prediction event signals vs orderbooks vs rankings. Descriptions cross-reference alternatives, so an agent can reliably choose the right tool.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with domain prefixes (news_events, news_feed, news_prediction). Verbs are get, search, list, explain, and nouns clearly describe the resource. No mixed conventions or vague names.

Tool Count5/5

18 tools is well-scoped for the server's broad read-only purpose covering news, social sentiment, prediction markets, and market-move reports. Each tool covers a distinct function without redundancy or bloat.

Completeness5/5

The tool surface covers the full read-only lifecycle: searching and filtering events, retrieving details, aggregating social signals, searching various sources, and accessing prediction market data. No obvious gaps for the stated domain; all necessary operations are present.