BytesAgain AI Skills Search

score_skills

Six-dimension skill scoring engine. Given a topic, searches skills and scores each on: downloads (25pts), stars (15pts), category relevance to topic (20pts, AI-evaluated), description quality (15pts), source diversity (15pts), name match (10pts). Use when you want to see how well skills rank for a task. Returns scored list sorted by total.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Number of skills to return scored. Default: 20. Max: 50.
`query`	Yes	Topic or task to score skills against. Example: "email automation", "data analysis". Required.

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations available, the description carries the full burden. It discloses the algorithm, including weighted scoring and AI-evaluated relevance, and states the output format ('Returns scored list sorted by total'). It does not explicitly mention being read-only, but the search/score nature implies no side effects.

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 two sentences, front-loaded with the core purpose, and efficiently packs scoring dimensions, weights, usage, and output into minimal text. Every sentence provides actionable information without waste.

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 description covers purpose, usage, scoring logic, and output type concisely. Since there is no output schema, it explains the return as a 'scored list sorted by total' but could be more explicit about the structure of each scored item; still, it is adequate for the agent's selection and invocation.

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 coverage is 100% and both 'query' and 'limit' already have clear descriptions. The description adds little beyond aligning 'Given a topic' with the query parameter; it does not enrich parameter meaning further.

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 states a specific verb ('searches skills and scores each') on a specific resource (skills) and details six scoring dimensions with weights. It clearly distinguishes itself from siblings like search_skills and evaluate_skill by emphasizing ranking behavior and the sorted output.

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

Usage Guidelines4/5

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

It explicitly says 'Use when you want to see how well skills rank for a task,' providing clear context. However, it does not mention alternatives or exclusions, so it stops short of full when-not guidance.

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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