EmojiDig Emoji Search

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real value by enumerating the returned fields (name, codepoints, category, version, aliases, keywords, skin-tone support, related emoji) in the absence of an output schema, though it says nothing about not-found or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence that opens with the verb and accepted inputs, then lists return fields. No filler, no repetition of the title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with no output schema, listing the return fields fills the main gap. The only omission is what happens on an unmatched character or slug, which an agent calling this would reasonably want to know.

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

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

Schema coverage is 100% and the schema already documents the single 'emoji' parameter. The description goes slightly beyond it by giving concrete examples of both accepted forms ("🫠" and "melting-face"), making the slug-vs-character choice unambiguous.

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

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

Specific verb+resource ('Look up one emoji') with the accepted identifier forms and an enumeration of the fields returned, so the agent knows exactly what it gets back. It never names the sibling search_emoji, so the contrast with the bulk-search tool is only implied by the word 'one'.

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

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

The phrase 'one emoji by the character itself ... or its EmojiDig slug' implies the single-item lookup case, but there is no explicit statement of when to use this rather than search_emoji, and no mention of behavior when the identifier is unknown.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing the return shape and ranking ('emoji characters, names and links, best match first'), but says nothing about result-count behavior, empty-result behavior, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the capability and followed by the return contract; the example list earns its space because it establishes the free-text nature of the query.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description usefully states what comes back and in what order, which is the key missing piece. The remaining gap is the undocumented limit parameter and lack of guidance on sibling selection, both minor for a simple read-only search.

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

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

Schema coverage is 0%, so the description carries the burden; it partly compensates by illustrating valid query strings ('happy', 'dead', 'fire', 'thank you', 'flag japan'), which conveys that natural language and multi-word phrases work. The limit parameter (default 10, max 50) and the 64-character query cap are entirely unaddressed by either schema or description.

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

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

States a specific verb and resource ('Find emoji') and enumerates the matching axes (meaning, mood, slang, name) with concrete example queries. It does not distinguish itself from the sibling get_emoji, so an agent must infer that this one is query-based lookup rather than exact retrieval.

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

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

The example queries implicitly tell the agent what kinds of input are appropriate, which is genuine usage guidance. However, there is no statement of when to prefer this over get_emoji, no note that the query is free-text rather than an exact emoji name/character, and no exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.