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Glama

Rawg

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?

Annotations already mark the tool read-only, idempotent, and non-destructive. The description adds substantial behavioral detail beyond that: graceful degradation when GLEIF/OpenFIGI are unavailable, explicit `unresolved` reporting, `figi_candidates` returned when ambiguity exists, source labeling for identifiers, and internal cascading across lookup endpoints. No contradiction with annotations.

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 information-dense and well front-loaded with examples and the "Use FIRST" directive. It is organized into SUPPORTED TYPES and value semantics, and nearly every sentence adds context. It loses one point because some details are redundant or could be tightened without losing meaning.

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?

There is no output schema, so the description carries the full burden of explaining return behavior. It thoroughly covers what identifiers are returned, how ambiguity is handled, what happens when sources fail, and what inputs are acceptable. An agent has enough information to select and invoke this tool correctly across the supported entity types.

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 high-value semantics that the schema alone lacks: the warning to pass the ENTITY NAME ONLY, the explanation that trailing security-class words break matching, the note that an ISIN resolves to the issuing legal entity, and the ticker/CIK/name input variety for company type. This materially improves agent invocation correctness.

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 opens with a clear, specific verb phrase: "resolve a user-spoken NAME to the canonical/official identifiers other tools require as input." It then enumerates supported entity types (company, drug) and concrete identifier outputs (CIK, LEI, FIGI, RxCUI), which clearly differentiates it from sibling tools like entity_profile or validate_claim.

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 states an explicit trigger: "Use FIRST whenever you have a name but need an ID," which is strong routing guidance. It also explains that the tool replaces multiple manual lookups, but it does not name alternatives or give explicit when-not-to-use conditions, 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

A3.6/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx_beta is explicitly identical to ask_pipeworx, bet_research overlaps heavily with polymarket_edges, and entity_profile/recent_changes/compare_entities/validate_claim all pull from the same SEC/news fundamentals space. The memory trio and game lookup tools are distinct, but too many other tools could be confused for one another.

Naming Consistency3/5

The surface is uniformly snake_case and has some strong families (list_*, polymarket_*, ask_pipeworx_*), but it mixes verb-led names (search_games, remember, validate_claim) with noun-led names (entity_profile, polymarket_arbitrage, pipeworx_trending) and brand-style names like ask_pipeworx. There is a pattern, but it is not a single consistent one.

Tool Count2/5

35 tools is a heavy surface, and the set feels sprawling rather than focused: a four-tool RAWG game submodule sits alongside a general-purpose research platform, Polymarket edge tooling, memory helpers, subscriptions, feedback, and meta-utilities. Many of these could have been consolidated or split into separate servers.

Completeness3/5

As a general data-research and prediction-market platform the coverage is strong, with lookup, grounded verification, entity resolution, research fan-out, and subscription flows. But for a server named Rawg, the game domain is thinly covered with only search/get/list tools and no game-detail enrichment or broader browsing surface, leaving the core domain feeling like an afterthought.

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