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Barcelona Events

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

A5/5.0
Behavior5/5

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

Annotations already cover read-only, open-world, and idempotent behavior, and the description adds substantial operational context: internal cascading through multiple lookup endpoints, graceful degradation when GLEIF/OpenFIGI is unavailable, ambiguous-match handling via figi_candidates, source labeling for identifiers, and explicit reporting of unresolved identifiers. None of this 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 information-dense and structurally organized: examples, core purpose, supported types, edge-case behavior, and usage instruction. There is no filler; each sentence earns its place by adding a behavioral rule, an example, or a constraint an agent needs to call the tool correctly.

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 tool with no output schema and high internal complexity, the description is remarkably complete. It covers accepted inputs, ownership enrichment, how ambiguity is surfaced, fallback behavior when upstream sources fail, and what the response reports (identifiers, sources, unresolved). An agent has enough context to invoke this tool correctly across its main scenarios.

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?

Despite 100% schema description coverage, the description enriches both parameters: it explains the type enum, gives concrete examples for ticker/CIK/name/brand/generic inputs, and provides crucial parsing guidance for value—especially the bond issuer caveat. This is meaningfully beyond what the schema alone offers.

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 user queries and immediately states the core function: resolving a user-spoken name to canonical/official identifiers that other tools require. It also enumerates supported entity types and frames the tool as the first step in a workflow, clearly distinguishing its role from siblings that consume identifiers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs 'Use FIRST whenever you have a name but need an ID,' then clarifies accepted input formats for both supported types. It even provides a negative example for bond issuer names, warning against including trailing security-class words that would break the lookup. This is concrete, actionable routing guidance.

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

Many tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual queries with subtle differences, and the Polymarket suite (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker) has fine-grained distinctions that are hard to separate. The single Barcelona events tool is isolated and unrelated to the rest, adding to agent confusion.

Naming Consistency3/5

Most tool names use snake_case and many follow a verb_noun pattern, but there are notable inconsistencies: noun-first names (entity_profile, polymarket_arbitrage, pipeworx_trending) and modifiers like beta/grounded on ask_pipeworx introduce non-uniformity. Overall the set is readable but not consistently predictable.

Tool Count2/5

With 32 tools, the set is beyond the well-scoped 3-15 range. The count is especially inappropriate for a server named 'Barcelona Events' because only one tool actually relates to Barcelona events; the other 31 are a broad data-research and utility collection with no clear connection to the server's apparent purpose.

Completeness1/5

For a server named 'Barcelona Events', the surface is severely incomplete: it offers a single events search tool with no create, update, delete, detail, venue, or organizer operations. Even interpreting the domain broadly, the mismatch between the server name and the tool set leaves a critical gap between user expectation and actual capability.

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