Skip to main content
Glama

Trakt

by io.github.pipeworx-io

Entity Profile

entity_profile
Read-onlyIdempotent

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO, news, GLEIF and returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today; person/place coming soon.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193"). Names not supported — use resolve_entity first if you only have a name.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, etc. Description adds soft-fail for patents, news fallback, and return field details 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?

Single paragraph with example queries upfront and structured list of returns. Slightly verbose but well-organized.

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?

No output schema, but description thoroughly explains all return fields, data sources, and edge cases (soft-fail, fallback). Complete for a 2-param tool.

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%. Description adds context like zero-padded CIK requirement and that type is only 'company', going beyond 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?

Clearly states it returns a full cross-source profile of a US public company in one call, listing data sources and fields. Distinguishes from chaining single-pack lookups.

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 'ALWAYS PREFER over chaining...' and specifies supported inputs (ticker/CIK, not names) with a fallback to resolve_entity.

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

All Trakt 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

A3.8/5.0
Disambiguation2/5

The tool set has significant overlap among query and research tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research) and among entity/company tools (entity_profile, compare_entities, recent_changes). Despite detailed descriptions, an agent would struggle to select the correct tool without careful reading, especially for nuanced differences.

Naming Consistency2/5

Tool naming is inconsistent: some start with verbs (ask_, generate_, validate_, scan_, subscribe) while others are nouns (entity_profile, popular, trending, search, recent_alerts, recent_changes). The snake_case style is consistent, but the verb_noun pattern is not, making predictions of tool names difficult.

Tool Count3/5

38 tools is on the high side for a single server, but the scope is broad (general query, research, Trakt, subscriptions, memory). The count is appropriate for the wide range of functionality, though some tools could be merged to reduce cognitive load.

Completeness4/5

The tool set covers a very wide range of tasks: querying, research, entity profiles, comparisons, subscriptions, memory, Trakt operations, etc. For the Trakt domain, it has all essential operations (search, get, list, trending). The Pipeworx side has a comprehensive set for data access, grounding, and validation. Minor gaps exist (e.g., no update for subscriptions), but overall it is well-covered.

Resources