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BytesAgain AI Skills Search

by com.bytesagain

get_skill

Fetch full details for one skill by slug. Call AFTER search_skills or popular_skills when a user selects a specific result — do NOT batch-call for every item. Returns: name, description, category, tags, version, author, downloads, stars, install_command, homepage_url, repo_url. Error lifecycle: slug not found → {error: "Skill not found"} → fall back to search_skills with related keyword. Never guess slugs; only use slugs from prior tool results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesExact slug string from a prior search_skills or popular_skills result. Format: lowercase, hyphen-separated (e.g. "chart-generator"). Never guess or modify slugs. Required — no default.

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries full behavioral burden and delivers: it lists the return fields, defines the error lifecycle for a missing slug, and warns against guessing slugs. This is strong behavioral disclosure for a simple read tool.

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 compact and front-loaded with the core purpose, followed by terse guidance and error behavior. Every sentence carries meaningful information, and the structure flows logically from purpose to usage to fallback.

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 one-parameter read tool with no output schema, the description is complete: it enumerates return fields, explains the error response, and positions itself within the tool family. No critical behavioral or usage detail is missing.

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

Parameters4/5

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

The input schema already documents the slug format and requiredness at 100% coverage. The description adds useful integration context ('only use slugs from prior tool results') and reinforces the 'never guess' rule, adding modest semantic value 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 starts with a specific verb+resource: 'Fetch full details for one skill by slug.' It clearly distinguishes from sibling tools like search_skills and popular_skills by emphasizing single-skill detailed retrieval rather than list or search behavior.

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 explicitly states when to use this tool: 'Call AFTER search_skills or popular_skills when a user selects a specific result.' It also provides a negative directive ('do NOT batch-call for every item') and a concrete fallback path to search_skills on error, making usage guidance exceptionally clear.

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.

Resources