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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.

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses rich behavioral detail: resolution cascades through multiple endpoints, LEI/FIGI enrichment degrades gracefully when upstream services are unavailable, unresolved identifiers are explicitly listed under `unresolved`, and ambiguous matches return `figi_candidates` rather than asserting a false single answer. No described behavior contradicts the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but densely packed, front-loaded with trigger phrases and the core instruction before moving into per-type details. Each sentence earns its place: the ISIN behavior, non-equity resolution, candidate-list behavior, and graceful degradation all address scenarios an agent would otherwise have to learn by trial and error.

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?

With no output schema, the description carries the full burden of explaining return behavior, and it does so thoroughly: source-labelled identifiers, `unresolved` listings, `figi_candidates`, RxNorm citations, and degradation when GLEIF/OpenFIGI fail. An agent has enough information to call this tool correctly and to interpret ambiguous or incomplete results.

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?

Although the input schema already documents both parameters at 100% coverage, the description adds substantial call-safety guidance: accepted input forms (ticker, CIK, ISIN, name), the warning to pass only the issuer as printed for bonds, and why trailing security-class words break FIGI matching. This materially helps an agent construct correct `value` arguments beyond the schema's 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?

The description opens by mapping many concrete user phrasings ("What's the ticker for…", "find the CIK for…") to a single clear job: resolving a spoken name to canonical identifiers other tools require as input. It distinguishes resolve_entity from siblings by positioning it as the identity-lookup entry point, and it enumerates exactly what each supported type produces.

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 rule — "Use FIRST whenever you have a name but need an ID" — which tells an agent when to select this tool. It also clarifies ambiguous bond-name cases and instructs callers to pass only the entity name, but it does not explicitly name sibling alternatives or state when NOT to use resolve_entity.

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

B3.3/5.0
Disambiguation1/5

The tool set includes multiple overlapping tools for predictions (bet_research, polymarket_arbitrage, polymarket_edges, etc.) and data lookups (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and mixes blockchain tools with unrelated services, making it difficult for an agent to select the correct tool.

Naming Consistency1/5

Tool names follow no consistent pattern: some use verb_noun (get_address, list_chains), others are multi-word phrases (ai_visibility_check, compare_entities), and styles mix snake_case and camelCase erratically.

Tool Count2/5

With 39 tools, the surface is bloated for a blockchain explorer. Many tools are unrelated to blockchain, inflating the count well beyond what is necessary for the server's stated purpose.

Completeness1/5

The server is named 'Blockscout' but includes mostly non-blockchain tools, leaving the blockchain domain severely incomplete. Even the blockchain-specific tools miss common operations like event logs or internal transactions.