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artic

by io.github.pipeworx-io

Resolve Entity

resolve_entity
Read-onlyIdempotent

"What's the ticker for…" / "find the CIK for…" / "what's the LEI for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" / "who owns X" / "is X a subsidiary of Y" — resolve a user-spoken NAME to the canonical/official identifiers other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (cross-source identity spine: 10-digit CIK + ticker + company_name from SEC EDGAR, legal-entity LEI from GLEIF with parent/ultimate-parent/children ownership when the LEI resolves, and security FIGI from OpenFIGI — by exact ticker map when a ticker is implied, and otherwise by name search, so NON-EQUITY instruments that never have a ticker (municipal and corporate bonds, notes, authority debt) DO resolve here; when a name matches more than one instrument it asserts nothing and returns figi_candidates to pick from, which is the correct answer to an issuer name that does not identify a single bond; every identifier is labelled with the source that established it, and an identifier that could NOT be resolved is stated explicitly under unresolved rather than omitted — accepts ticker, CIK, ISIN, or company name as input; an ISIN like "CH0038863350" resolves to the LEGAL ENTITY that issued the security via the GLEIF ISIN-to-LEI mapping, covering non-US issuers EDGAR cannot reach), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/concept/{rxcui} citation; accepts brand or generic name). LEI/FIGI enrichment degrades gracefully — if GLEIF or OpenFIGI is unavailable, the EDGAR identifiers still return. Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type: "company" or "drug".
valueYesFor company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., "ozempic", "metformin"). Pass the ENTITY NAME ONLY — for a bond that is the ISSUER exactly as printed ("NEW YORK ST DORM AUTH"), never the question's full noun phrase ("NEW YORK ST DORM AUTH revenue bonds"): the FIGI lookup matches instrument names, so trailing security-class words match nothing.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / value / description
      Previous value: -"For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., \"ozempic\", \"metformin\")."New value: +"For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., \"ozempic\", \"metformin\"). Pass the ENTITY NAME ONLY — for a bond that is the ISSUER exactly as printed (\"NEW YORK ST DORM AUTH\"), never the question's full noun phrase (\"NEW YORK ST DORM AUTH revenue bonds\"): the FIGI lookup matches instrument names, so trailing security-class words match nothing."
  2. Changed3 schema fields changed
    • changedInput schema / properties / type / description
      Previous value: -"Entity type. v1 supports \"company\"."New value: +"Entity type: \"company\" or \"drug\"."
    • changedInput schema / properties / type / enum
      Previous value: -[
-  "company"
-]New value: +[
+  "company",
+  "drug"
+]
    • changedInput schema / properties / value / description
      Previous value: -"Ticker, CIK, or company name (e.g., \"AAPL\", \"0000320193\", \"Apple\")."New value: +"For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., \"ozempic\", \"metformin\")."
  3. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark it read-only/idempotent, and the description adds meaningful non-obvious behavior: cascading lookups, graceful degradation if GLEIF/OpenFIGI is unavailable, ambiguous matches returned as figi_candidates, and unresolved identifiers explicitly listed. No contradiction with readOnlyHint/openWorldHint.

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 long, but densely useful and organized via SUPPORTED TYPES and value-guidance sections with the main use-case front-loaded. It is slightly overstuffed with parentheticals and examples for a two-parameter tool, so not a perfect conciseness score.

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?

For a tool with no output schema, the description covers inputs, outputs (CIK/ticker/LEI/FIGI/RxCUI, unresolved, figi_candidates), failure modes, and fallback behavior. An agent has everything needed to select and correctly invoke it across company and drug lookups.

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?

Though schema coverage is 100%, the description adds critical semantics beyond the schema: pass the entity name only, use the issuer exactly as printed for bonds, and avoid trailing security-class words. It maps example inputs (AAPL, 0000320193, ozempic) to the value parameter and explains type behavior.

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 uses a precise verb ('resolve') against a clear resource (user-spoken names to canonical/official identifiers) and enumerates supported entity types and identifier systems (CIK, LEI, FIGI, RxCUI). It distinguishes itself from siblings by stating it is the first stop when a name but no ID is available, not a profile or comparison tool.

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?

Explicitly says 'Use FIRST whenever you have a name but need an ID' and gives concrete query phrasings plus supported types. It does not explicitly name alternatives or when-not-to-use, so it stops short of a full 5.

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

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TDQS

A3.9/5.0
Disambiguation4/5

Most tools are carefully delineated with explicit use-case guidance; ask_pipeworx, ask_pipeworx_grounded, and deep_research are clearly separated by depth and grounding. The main weak spots are ask_pipeworx_beta, which is a current functional duplicate of ask_pipeworx, and the several prediction-market/company-research tools that still require careful reading to pick correctly.

Naming Consistency4/5

Names are uniformly snake_case and mostly command-like, with coherent families such as polymarket_*, ask_pipeworx_*, get_art*, subscribe/unsubscribe, and remember/recall/forget. The pattern is not strictly verb_noun throughout, since noun phrases like entity_profile, pipeworx_trending, and recent_changes appear, but the inconsistency is minor and readable.

Tool Count2/5

35 tools is well past the 25+ threshold for a single MCP server, and the set bundles Art Institute lookups, Pipeworx data research, prediction-market analysis, memory, subscriptions, and website utilities into one place. Many tools earn their keep individually, but the overall toolbox feels bloated and poorly scoped.

Completeness3/5

The Pipeworx, memory, and subscription subgroups have decent lifecycle coverage: remember/recall/forget and subscribe/unsubscribe/listsubscriptions/recent_alerts form coherent loops. But relative to the 'artic' server name, the Art Institute surface is thin—there is no artist search and no exhibition-detail tool—and the unrelated embedded domains prevent the set from feeling complete for any one clear purpose.

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