Skip to main content
Glama

Packagist

by io.github.pipeworx-io

Scan Competitor AI Presence

scan_competitor_ai_presence
Read-onlyIdempotent

Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns ranked list with score, confidence, signal density per entity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsNoWhich models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKeyNoOptional Anthropic API key — only if "anthropic" is in models. Passed to api.anthropic.com per probe.
contextNoOptional shared context applied to every probe (e.g. "B2B SaaS", "Boston restaurant"). Disambiguates common names.
entitiesYesArray of 2-8 entities to compare (brand/business/product names). First entry treated as the "subject" for narrative; rest are competitors.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations indicate read-only, idempotent, non-destructive behavior. The description adds context: it probes each entity with ai_visibility_check, ranks results, and surfaces most/least recognized. It also describes the return format (score, confidence, signal density), going 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.

Conciseness5/5

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

The description is concise (4 sentences) and well-structured: purpose first, then mechanism, use case, and return format. No unnecessary information.

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?

Despite no output schema, the description explains the return format (ranked list with score, confidence, signal density). Parameters are fully documented in schema. The tool's behavior of calling ai_visibility_check is transparent. Complete for its 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%, so baseline is 3. The description adds value by clarifying that models defaults to 'workers-ai' if omitted and that an API key is needed for 'anthropic' model. This provides context not in 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 states the tool's purpose: 'Compare AI visibility across multiple entities side-by-side.' It specifies the verb 'compare' and resource 'AI visibility', and distinguishes from sibling tools like ai_visibility_check (single entity) and compare_entities (general comparison).

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 provides a clear use case: 'Useful for competitive AI-marketing audits' with an example question. It implies when to use this over ai_visibility_check but does not explicitly list when not to use or other alternatives.

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

All Packagist 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

B3.3/5.0
Disambiguation2/5

Many tools have overlapping purposes: ask_pipeworx_beta is a literal duplicate of ask_pipeworx, and ai_visibility_check/scans overlap with each other while the many prediction-market and edge tools cover similar ground. The verbose descriptions help somewhat, but an agent would frequently struggle to pick the right tool.

Naming Consistency2/5

Naming is inconsistent: some tools use verb_noun (get_package, list_versions), others noun_verb (ai_visibility_check, bet_research), and several are brand-specific (pipeworx_feedback, pipeworx_trending) with no uniform verb style. The mixed patterns make it hard to predict tool names.

Tool Count1/5

35 tools is far too many for a server named Packagist: only 4-5 tools relate to the PHP/Composer registry while the vast majority concern Pipeworx data lookups, Polymarket analysis, and memory utilities. The scope is severely mismatched with the server's name and apparent purpose.

Completeness2/5

For a Packagist registry server, the core read operations (search, get, list versions, stats) are present, but the server is cluttered with unrelated functionality and offers no package management actions. The tool set is not complete for any single, coherent domain, making it feel like two different servers merged into one.

Resources