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Chaos Index

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

A4.4/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint false), the description adds important behavioral details: graceful degradation, bundlephobia timeout (5-30s), and partial failure handling. This enriches the agent's understanding of tool behavior.

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 information-dense and front-loaded with the core purpose, but slightly long. Every sentence adds value without fluff. Good structure, but could be slightly more concise.

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 thoroughly details return fields (summary block, per-advisory detail, links, alternative versions) and error handling. It covers all necessary context for an agent to understand what the tool returns and how it behaves.

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 covers 100% of parameters with clear descriptions. The description reinforces scoped package acceptance and default version behavior, but does not add significant new semantics beyond what the schema provides. Baseline score for high schema coverage.

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 it performs a composite check for npm packages, specifies the verb 'scan dependency', and defines the resource as an npm package. It explicitly distinguishes scope (NPM ecosystem only) and mentions fallback for other ecosystems, helping differentiate from potential alternatives.

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?

Provides explicit use cases: 'whenever an agent asks 'is X safe / popular / small' or 'what does adding lodash cost me'. It also mentions limitations (NPM only in v1) and suggests alternatives for other ecosystems. Lacks explicit 'when not to use' but the context is clear.

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

All Chaos Index toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

The set contains multiple near-duplicate entry points: ask_pipeworx, ask_pipeworx_beta (explicitly identical right now), and ask_pipeworx_grounded overlap heavily, while deep_research, discover_tools, and suggest_questions all claim to be the 'call this first' tool. Also, ai_visibility_check vs scan_competitor_ai_presence and the five polymarket_* tools create boundaries an agent could easily mischoose.

Naming Consistency4/5

Most tools follow a clear snake_case verb_noun pattern (compare_entities, validate_claim, unsubscribe, search_within). Minor deviations exist — chaos_index_calculate puts the verb last, entity_profile is noun-only, and the pipeworx_ prefix is applied inconsistently (pipeworx_trending vs ask_pipeworx) — but the overall style is predictable.

Tool Count2/5

32 tools is too many for a coherent single-purpose server; the set spans data routing, prediction markets, subscriptions, memory, AI visibility, npm scanning, and llms.txt generation. It reads as a bundled suite of unrelated utilities rather than a focused tool surface.

Completeness3/5

Subdomains are individually fairly complete: subscription CRUD, memory CRUD, and the prediction-market workflow (research, edges, arbitrage, fill risk, tracking) are all covered. However, the overall domain is incoherent, and gaps exist such as no update-subscription operation and no way to modify an existing memory beyond overwriting via remember.

Resources