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emojihub

by io.github.pipeworx-io

Get By Group

get_by_group
Read-onlyIdempotent

Search emojis by group (e.g., "face-positive", "face-negative", "animals-mammal", "hand-fingers-open"). Returns matching emojis with names and categories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupYesThe emoji group slug, e.g. "face-positive", "face-negative", "animals-mammal".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of emojis in the group
groupYesThe requested emoji group
emojisYesArray of emojis in the group

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, lowering the burden. The description adds value by specifying the return content (names and categories) and providing concrete group examples, which is useful context beyond the 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?

The description is a single, well-structured sentence that front-loads the main action ('Search emojis by group') and includes useful examples. Every word contributes, with no fluff or 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?

For a simple one-parameter tool with an output schema and strong annotations, the description is complete. It states the purpose, gives valid parameter examples, and mentions the return fields. No critical information is missing for effective use.

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%, and the schema already provides the group parameter description with examples. The description repeats the same examples, adding no significant semantic meaning beyond what the schema offers, so the baseline of 3 applies.

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

Purpose4/5

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

The description clearly states the tool searches emojis by group and provides specific group slug examples, making the purpose distinct. However, it does not explicitly differentiate from the sibling tool get_by_category, so it falls short of a 5.

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

Usage Guidelines3/5

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

The description implies usage through group examples and the stated search action, but it offers no direct guidance on when to use this tool versus alternatives like get_by_category. There is no explicit when-to-use or when-not-to-use context.

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

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there is some overlap among the numerous Pipeworx query and prediction market tools (e.g., polymarket_arbitrage vs. polymarket_edges vs. polymarket_fill_risk). Descriptions help differentiate them, so the ambiguity is minor.

Naming Consistency3/5

Tool names use a mix of verb_noun patterns (e.g., list_subscriptions, validate_claim), phrases (ask_pipeworx, bet_research), and standalone nouns (pipeworx_feedback). While readable, the lack of a single consistent convention makes the set feel less cohesive.

Tool Count3/5

33 tools is on the high side, with many highly specialized prediction market and Pipeworx management tools. The server's name 'emojihub' suggests a narrow focus, but the actual scope is much broader, making the count feel somewhat inflated for its apparent purpose.

Completeness4/5

The tool set covers a vast domain: factual data retrieval, company profiles, comparisons, claim validation, prediction market analysis, memory, subscriptions, and emoji lookup. Minor gaps exist (e.g., no direct tool for simple web search), but overall coverage is comprehensive.

Resources