Skip to main content
Glama

Entertainment Feeds

by io.github.pipeworx-io

Scan Dependency

scan_dependency
Read-onlyIdempotent

Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesnpm package name. Scoped packages (e.g. "@types/node") are accepted.
versionNoSpecific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent, etc.), the description reveals fan-out across two APIs (deps.dev, bundlephobia), partial failure degradation with 'sources_failed', and timing details (bundlephobia first measurement 5-30s). This adds significant behavioral context without contradiction.

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 detailed but each sentence contributes essential information: composite nature, usage guidance, return format, and limitations. While slightly long, it is well-structured and free of fluff.

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?

Given no output schema, the description lists all return fields (summary block, advisories, links, alternative versions) and explains data sources and failure modes. For a complex composite tool, this is highly complete.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds value by explaining that scoped packages are accepted for 'package' and that 'version' defaults to latest when omitted. This enriches the semantic understanding beyond the schema descriptions.

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 is a composite check for deciding whether to add an npm package, covering license, security, bundle size, and more. It specifies the verb 'scan' and resource 'dependency', and distinguishes from sibling tools which are unrelated (e.g., betting, AI visibility).

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?

Explicitly says 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. Also notes NPM-only in v1 and directs to deps.dev:version for other ecosystems, providing clear when-to-use and when-not-to alternatives.

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

All Entertainment Feeds 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

A3.6/5.0
Disambiguation3/5

While most tools have distinct purposes, there is notable overlap between the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and deep_research. Similarly, bet_research and polymarket_edges both analyze betting opportunities. These overlapping tools can cause confusion for an agent.

Naming Consistency2/5

Tool names follow a snake_case pattern, but the verbs used are highly varied (ask_, bet_, compare_, deep_, discover_, entity_, fetch_, forget_, generate_, list_, pipeworx_, polymarket_, read_, recall_, recent_, remember_, resolve_, scan_, search_, subscribe_, suggest_, unsubscribe_, validate_). This lack of a consistent verb_noun pattern makes it harder to predict tool names.

Tool Count2/5

34 tools is excessive for an 'Entertainment Feeds' server. The majority of tools are unrelated to entertainment (e.g., SEC filings, FDA drugs, FRED data, Polymarket betting). Many of these should belong to a separate 'data-access' server, making the scope unwieldy and unfocused.

Completeness2/5

For an entertainment feeds server, the set is incomplete. It can list and read curated feeds and fetch arbitrary RSS, but lacks tools for managing subscriptions to those feeds, searching across feeds, or creating feeds. The inclusion of many non-entertainment tools doesn't compensate for these gaps.

Resources