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Glama

Wynncraft

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. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description adds substantial behavior beyond the annotations: cascading internal lookups, graceful degradation when GLEIF/OpenFIGI are unavailable, returning figi_candidates rather than asserting on ambiguous matches, labeling identifier sources, and listing unresolved identifiers explicitly under `unresolved`. No contradiction with readOnly/idempotent hints.

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 front-loaded with user-intent examples and the 'Use FIRST' rule, and the dense details are mostly relevant. However, it is a very long single block with some parenthetical editorializing (e.g., 'which is the correct answer to an issuer name that does not identify a single bond'), which slightly reduces scannability.

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 having no output schema, the description conveys the expected results for both entity types, fallback behavior, ambiguity handling, and unresolved-identifier reporting. For a complex multi-source resolver, this is enough for an agent to invoke it and interpret the response.

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 still contributes crucial semantics: accepted input forms (ticker, CIK, ISIN, name), ISIN-to-LEI resolution, the bond-issuer exactness rule, and the instruction to pass the entity name only. This goes well beyond the schema's brief examples.

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?

Description states a specific action and resource: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It immediately distinguishes itself as the ID-resolution entry point with 'Use FIRST whenever you have a name but need an ID' and enumerates exactly which entity types it covers.

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 gives an explicit trigger ('Use FIRST whenever you have a name but need an ID') and rich query examples. It does not name alternative sibling tools or state when not to use it, so the when-not/alternatives portion is less explicit than the ideal.

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

B3.1/5.0
Disambiguation2/5

The set is split between Wynncraft game data tools and a large Pipeworx data cluster, and within the Pipeworx cluster there is heavy overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (the beta is currently identical), ai_visibility_check and scan_competitor_ai_presence do essentially the same thing at different granularities, and six polymarket_* tools cover overlapping prediction-market functionality. An agent would frequently struggle to choose the right tool.

Naming Consistency3/5

Snake_case with a mostly verb_noun pattern dominates (ask_pipeworx, compare_entities, resolve_entity, validate_claim), and families like polymarket_* and pipeworx_* are internally consistent. However, there is a notable mix of noun-only tools (guild, item_database, leaderboard, player, news) and the server is named Wynncraft while the majority of tools are Pipeworx-branded, which breaks overall coherence.

Tool Count2/5

40 tools is well beyond the borderline range, and the count is inflated by redundancy: multiple ask_pipeworx variants, several overlapping polymarket tools, a memory trio, and subscription management that arguably belong to a separate server. The Wynncraft portion alone would be nicely scoped (~9 tools), but the merged surface feels heavy and unfocused.

Completeness4/5

The Wynncraft side offers solid read coverage of players, guilds, items, leaderboards, news, and online status, which is appropriate for the domain. The Pipeworx side covers lookup, grounded verification, comparison, research, prediction markets, subscriptions, memory, and feedback, leaving few obvious dead ends for the stated meta-purposes.

Resources