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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

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, and idempotent behavior, and the description adds substantial non-obvious detail: graceful degradation when GLEIF/OpenFIGI are unavailable, ambiguous matches returning figi_candidates rather than asserting an answer, unresolved identifiers being explicitly reported, and internal cascading across multiple lookup endpoints. This goes well beyond what structured annotations provide.

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 dense but organized: trigger phrases, supported types, and the primary use rule are front-loaded, and later caveats about ambiguity and degradation earn their place. It is long, but the length is justified by the complexity of the entity-resolution behavior.

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 burden of explaining return semantics. It covers ambiguous candidates, unresolved identifiers, identifier source labeling, non-US issuer resolution, and degraded enrichment. For a complex tool with multiple entity types and cascading lookups, nothing critical is missing for selecting and invoking it correctly.

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 description coverage is 100%, but the description still adds high-value parameter meaning: for company it clarifies CIK formatting, source coverage, and ISIN-to-LEI resolution; for value it explicitly warns to pass the entity name only, gives example formatting for bond issuers, and explains why trailing security-class words break matching. This is genuinely additive beyond the schema.

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 concrete trigger phrases and a clear verb–resource mapping: resolve a user-spoken name to official identifiers. It also positions the tool against siblings by stating that other tools require these identifiers as input, so an agent can distinguish it from entity_profile or compare_entities without opening their schemas.

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 explicit guidance: 'Use FIRST whenever you have a name but need an ID,' plus many examples of when to invoke it. It does not explicitly enumerate exclusions versus specific alternatives like entity_profile, but the usage context is strong enough that an agent can reliably select the tool.

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

A3.5/5.0
Disambiguation2/5

Several tools have near-identical or heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx and validate_claim both answer factual questions, and discover_tools and suggest_questions both surface capabilities. The dense set of Polymarket and entity-research tools further blurs boundaries despite long descriptions.

Naming Consistency3/5

Names are consistently snake_case, but they do not follow a single predictable verb_noun pattern: actionable names like ask_pipeworx, search_projects, and compare_entities mix with noun-style names like polymarket_edges, pipeworx_feedback, and recent_changes. The convention is readable but not uniform.

Tool Count2/5

34 tools exceeds the reasonable scope for a coherent server, and many are near-duplicate variants or members of sprawling tool families (ask_pipeworx variants, multiple Polymarket scanners, several meta/discovery tools). The set would be stronger with consolidation around a smaller number of distinct capabilities.

Completeness1/5

If this server is meant to provide OSF access, the surface is severely incomplete: only search_projects, search_preprints, and get_project exist, with no create/update/delete, file handling, registration, or contributor access. If it is meant to be a broader Pipeworx assistant, the OSF tools are unrelated and the domain is so scattered that coverage is incoherent.