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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

A4.6/5.0
Behavior5/5

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

The description adds substantial behavioral detail beyond the annotations: multi-match handling via figi_candidates, explicit unresolved listing, graceful degradation when GLEIF/OpenFIGI are unavailable, source labelling for identifiers, and internal cascading across lookup endpoints. This is precisely the contextual information an agent needs to interpret ambiguous or partial results.

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

Conciseness3/5

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

The description is front-loaded with purpose and the 'Use FIRST' directive, but it quickly becomes one dense block of long parentheticals and asides. Some sentences, such as 'using resolve_entity replaces 2-3 manual lookups' and the explanatory note on ambiguous bond names, add value but could be trimmed without losing invocation-critical content.

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 two-parameter tool with no output schema, the description covers input variants, supported entity types, edge cases, source systems, and likely response elements such as figi_candidates and unresolved. An agent has enough information to invoke the tool correctly and interpret unusual outcomes.

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?

Even though schema coverage is 100%, the description adds critical parameter semantics: for bond lookups, pass the issuer exactly as printed and never the full noun phrase, because the FIGI lookup matches instrument names. This significantly reduces the risk of malformed queries beyond what the schema examples convey.

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 example queries and a direct purpose statement: resolving a user-spoken name to the canonical identifiers other tools require. It clearly distinguishes its scope by enumerating supported types (company, drug) and the identifier authorities involved (CIK, LEI, FIGI, RxCUI), making the tool's role unmistakable.

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?

It gives an explicit directive: 'Use FIRST whenever you have a name but need an ID,' and it lists several query intents. However, it never names a sibling tool or states when not to use it, so the when-not/alternatives portion of the guidance is only implied rather than explicit.

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 mixes two unrelated domains — Bitcoin mempool explorer tools and the much larger Pipeworx data-query platform — and within the Pipeworx half several tools route to the same 5,743-tool catalog (ask_pipeworx, deep_research, discover_tools, suggest_questions). ask_pipeworx_beta is currently an exact behavioral duplicate of ask_pipeworx, and the polymarket_* family has fuzzy boundaries (arbitrage vs edges vs fill_risk, with fill-checking living in both polymarket_arbitrage and polymarket_fill_risk), so an agent must read long descriptions to avoid misselection.

Naming Consistency3/5

All names use snake_case and there are recognizable sub-families (get_* Bitcoin lookups, ask_pipeworx_*, polymarket_*), but conventions are mixed across the whole set: bare-noun state tools (block_height, hashrate, mempool_stats, mining_pools) sit beside verb_noun actions (get_block, list_subscriptions), and prefix placement is inconsistent (ask_pipeworx vs pipeworx_trending/pipeworx_feedback). The naming is readable but not predictable enough to guess a tool's name from its function.

Tool Count2/5

41 tools is well past the 25+ threshold for a coherent server, and the count is inflated by bundling two unrelated products under a server named after only the smaller half (~10 Bitcoin tools vs ~31 Pipeworx tools). Many Pipeworx tools are convenience wrappers around one universal router, adding surface area without adding genuinely new capabilities.

Completeness3/5

Each half is internally workable: the Bitcoin side covers blocks, transactions, addresses, fees, hashrate, and pools, while the Pipeworx side provides broad query, research, subscription, and memory lifecycles. However, there are notable gaps relative to each domain (no block-list/fee-history endpoints on the explorer side; no direct per-source CRUD on the data side), and no single coherent domain is fully served because the server's stated identity matches only a fraction of its tools.