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Tfl

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.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare read-only and idempotent behavior, and the description adds rich context: multi-source identity resolution, graceful degradation when GLEIF/OpenFIGI is unavailable, explicit unresolved identifiers, figi_candidates on ambiguous matches, and internal cascading lookups. There is 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.

Conciseness3/5

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

Front-loaded with question patterns and a clear directive, but the body is a dense wall of text with long parentheticals that hurt scannability. Each detail is informative, so nothing is wasted, but the structure is not appropriately digestible for an agent.

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?

Given no output schema, the description carries full responsibility for explaining results, and it does: CIK, ticker, company_name, LEI, ownership, FIGI, figi_candidates, unresolved fields, source labels, RxCUI, ingredient, brand, and citation. Inputs, ambiguity handling, and failure behavior are all covered.

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%, yet the description still adds strong semantic guidance: accepted input forms for company versus drug, ISIN-to-LEI behavior, and the crucial warning that a bond value must be the issuer name exactly as printed, not the full noun phrase. This goes well 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?

States a specific action — resolve a user-spoken NAME to canonical/official identifiers — and supports it with concrete example queries. It also positions itself as the input step for other tools, distinguishing it from downstream siblings like entity_profile and compare_entities.

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?

Gives an explicit rule: 'Use FIRST whenever you have a name but need an ID,' and enumerates supported types and accepted input formats. It does not name sibling tools or state when to prefer alternatives, but the core use case is clearly scoped.

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

A3.7/5.0
Disambiguation3/5

Many tools have distinct purposes, but there are multiple ask_pipeworx variants and several Polymarket tools with similar functions, causing potential confusion. Most other tools are clearly differentiated, but the overlap in query and betting tools reduces clarity.

Naming Consistency2/5

Naming conventions are inconsistent: some tools use snake_case (ai_visibility_check), others use descriptive phrases (ask_pipeworx, generate_llms_txt), and some are very short (arrivals). Lengths vary widely, and there is no uniform pattern.

Tool Count2/5

37 tools is excessive for a coherent server; the scope is too broad, spanning transport, data lookups, prediction markets, and utilities. This suggests a lack of focus, making the server feel like a bundled collection rather than a well-scoped toolkit.

Completeness3/5

The server covers multiple domains but lacks depth. London transport tools are partial (e.g., no real-time tube positions), and domains like weather or stock quotes rely on the ask_pipeworx meta-tool rather than dedicated tools. The surface is broad but not comprehensively complete in any area.

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