BytesAgain AI Skills Search

search_use_cases

Search 1,000+ AI agent use-cases by task or goal description. Use-cases describe real-world workflows like "write a weekly report", "automate email replies", or "analyze sales data". Each use-case links to a dedicated page listing the best AI skills for that task. Use this tool when: (1) user describes a goal or workflow rather than a tool name, (2) user asks "how do I use AI for X", (3) you want to show what tasks AI can help with. Returns use-case slug, title, description, and page URL. Combine with search_skills to find specific tools for each use-case.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Number of use-cases to return. Default: 10. Max: 30.
`query`	Yes	Task or goal in natural language. Example: "write job descriptions", "automate social media", "analyze financial data".

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It explains the returned fields ('use-case slug, title, description, and page URL') and the relationship to dedicated pages. It does not explicitly state read-only behavior but 'search' implies it; lacks details on pagination or rate limits, which keeps it from 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.

Conciseness5/5

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

The description is well-structured, front-loaded with the main purpose, and every sentence adds value. The 'Use this tool when' list is concise and the combined mention of search_skills is relevant. It is appropriately sized for the information needed.

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?

The tool is simple (2 params, schema covers them), and the description provides return fields, usage conditions, and sibling relationship. Without an output schema, listing returned fields helps. Minor omissions like pagination are not critical for this search tool.

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?

The schema already covers both parameters with descriptions and examples, providing 100% coverage. The description adds context by framing 'query' as a task/goal description, but no additional parameter semantics beyond the schema.

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 clearly identifies the tool's purpose: 'Search 1,000+ AI agent use-cases by task or goal description.' It uses a specific verb ('Search') and resource ('use-cases'), and distinguishes from sibling tools like search_skills by focusing on goals/workflows rather than tool names, mentioning to 'Combine with search_skills.'

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?

The description provides explicit guidance with 'Use this tool when:' and lists three concrete scenarios (goal/workflow description, asking 'how do I use AI for X', showing what tasks AI can help with). It also directs users to combine with search_skills for specific tools, clearly differentiating use cases.

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

A4.1/5.0

Disambiguation3/5

Several tools have overlapping purposes: evaluate_skill and scan_skill both assess skill safety, while generate_usecase, get_workflow, and score_skills all involve skill scoring and recommendation. Description differences exist but boundaries are not always crisp, potentially causing misselection. The unrelated get_deals tool also adds confusion.

Naming Consistency4/5

Tool names mostly follow a consistent verb_noun snake_case pattern (e.g., search_skills, get_skill, submit_request). Minor inconsistencies exist: popular_skills uses an adjective instead of a verb, and generate_usecase uses 'usecase' while search_use_cases uses 'use_cases'.

Tool Count4/5

With 14 tools, the server is on the higher end of the typical range but still well-scoped for its broad functionality (search, evaluation, workflows, community, content pipeline). Each tool serves a distinct functional area, though a few could be consolidated.

Completeness4/5

The core workflow of searching, retrieving, and evaluating skills is well covered, including use cases and community requests. However, there are minor gaps such as lack of a category browsing tool or direct single-skill installation, and the inclusion of unrelated AliExpress deals seems out of place.

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