Skip to main content
Glama

Codewars

by io.github.pipeworx-io

AI Visibility Check

ai_visibility_check
Read-onlyIdempotent

Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass _apiKey to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityYesThe thing to ask about. Brand/business name, product name, person, or topic. E.g. "Pipeworx", "OpenInvoice", "Acme Corp pricing".
modelsNoWhich models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKeyNoOptional Anthropic API key (sk-ant-...) — only needed if "anthropic" is in models. Passed straight through to api.anthropic.com.
contextNoOptional: a phrase locating the entity (e.g. "Boston restaurant", "B2B SaaS"). Helps disambiguate common names.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive. The description complements these by explaining the probing behavior, per-model returns, default model (free), and that _apiKey is passed to Anthropic. It adds behavioral nuance (cost implication for Anthropic, multiple calls per model) that goes beyond annotations.

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 of four sentences, each carrying distinct information: core function, model/API key details, return structure, use cases. While dense, it is not wasteful. Could be split into bullet points for clarity, but current form is efficient.

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?

Given no output schema, the description adequately explains the return structure (per-model {score, confidence, signals, raw_response} + combined view). It covers all parameters, default behavior, and optionality. Minor omission: no explanation of what score 0-100 means (higher better), but overall complete for the tool's complexity.

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?

Schema coverage is 100%, but the description adds meaningful defaults ('Workers AI Llama-3.3-70b (free)') and explains the role of _apiKey and context. It clarifies that models array can be omitted to default workers-ai, and that context disambiguates entities. This enriches the parameter understanding.

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: 'Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model.' It uses a specific verb and resource, and the function is distinct from sibling tools like ask_pipeworx (general Q&A) or compare_entities (comparative analysis).

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?

The description includes explicit use-case guidance: 'Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.' It implies the tool is for visibility checks rather than general queries, but does not explicitly exclude scenarios or name alternative tools. Context is clear enough.

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

All Codewars toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

The 4 Codewars tools (kata, user, user_authored, user_completed) are distinct, but the 31 Pipeworx tools create real overlap: ask_pipeworx, ask_pipeworx_beta (explicitly 'currently matches ask_pipeworx exactly'), and ask_pipeworx_grounded are near-twins of the same router, and the five polymarket_* tools (edges, arbitrage, edge_tracker, fill_risk, kalshi_spread) have heavily overlapping opportunity-discovery purposes. discover_tools and suggest_questions also both serve as 'what can I ask' entry points. Agents will misselect between the three ask_pipeworx variants and across the prediction-market suite.

Naming Consistency2/5

Naming conventions are mixed: bare nouns (kata, user), bare verbs (forget, remember, subscribe), adjective_noun (recent_alerts, recent_changes), verb_noun (validate_claim, bet_research), and noun_verb (user_authored, user_completed) all appear. Even within the small Codewars family the prefix style is inconsistent — kata and user are bare nouns while user_authored and user_completed expect a user_ prefix, and remember/recall/forget use a different verb style than the rest of the server.

Tool Count2/5

35 tools exceeds the 25+ 'too many' threshold for a coherent server. Worse, 31 of the 35 are Pipeworx meta-research tools unrelated to the server's namesake (Codewars), so the count is drastically inflated relative to its apparent purpose — the server presents a full finance/prediction-market/research gateway while contributing only 4 tools to its advertised domain.

Completeness2/5

The actual Codewars surface has significant gaps: kata, user, user_authored, and user_completed are purely read-only, with no solution submission, attempt/training history, leaderboard access, or kata search by difficulty/language. Meanwhile the Pipeworx side is over-complete for a server not named for it, leaving the server's stated identity under-covered with no way to perform any write operation on the Codewars platform.

Resources