BytesAgain AI Skills Search

submit_request

Submit a new skill request to the BytesAgain community wall. Use when a user asks to publish a request for an AI skill they need. Creates a public entry on the requests wall. Sends notification to site admin. Input: title (one-line summary), request (10-800 chars), platform (optional), budget (optional), contact (required — email/TG for follow-up, kept private), nickname (optional display name).

Input Schema

TableJSON Schema

Name	Required	Description
`title`	No	One-line summary of the requested skill.
`budget`	No	Budget for the request, e.g. "$50" or "议价".
`contact`	Yes	Contact info (email/TG) — REQUIRED. Kept private, not shown publicly.
`request`	Yes	Detailed description of the skill needed — features, use case, and requirements. 10-800 characters.
`nickname`	No	Display name shown publicly on the wall.
`platform`	No	Target AI platform: OpenClaw, Claude Desktop, Cursor, Codex CLI, Copilot, Gemini CLI, or Other.

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations provided, the description takes on full burden. It discloses important behaviors: creates a public entry, sends notification to site admin, and keeps contact private. This goes beyond basic create semantics and informs the agent of 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.

Conciseness4/5

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

The description is a single paragraph that front-loads purpose and usage, followed by a compact parameter summary. It's slightly long due to enumerating all six params, but each part serves a purpose and no filler exists.

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?

For a 6-parameter tool with no output schema and no annotations, the description covers purpose, usage, parameters, and key side effects. It doesn't describe the return value, but for a submission tool this is acceptable without an output schema.

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%, so baseline is 3. The description restates parameters with brief clarifications (e.g., contact as 'email/TG for follow-up, kept private'), but adds limited new meaning beyond the schema. It's helpful but not significantly additive.

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 states the tool's purpose: submitting a new skill request to the BytesAgain community wall. It uses a specific verb ('submit') and resource ('skill request') and distinguishes from sibling tools like list_requests or search_skills by focusing on creation.

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?

Explicitly states when to use: 'Use when a user asks to publish a request for an AI skill they need.' This provides clear context, though it doesn't mention exclusions or alternatives directly, the intent is unambiguous given the sibling list.

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

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