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Remoteok

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 mark the tool as read-only/idempotent, and the description adds substantial behavioral detail: cascading internal lookups, graceful degradation when GLEIF or OpenFIGI is unavailable, ambiguity handling via figi_candidates, explicit unresolved identifiers, source labelling, and ISIN-to-LEI mapping. No contradictions.

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 front-loaded with query templates and a clear 'Use FIRST' directive. It is long and dense, especially the company-type parenthetical, but nearly every segment adds operational value; it could be tightened without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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 constraints, ambiguity behavior, unresolved-identifier handling, source labelling, and error degradation. It does not provide a full return-shape specification, but it is sufficient for an agent to select and invoke the tool 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?

Even though schema coverage is 100%, the description adds crucial operational rules: pass only the entity name, avoid trailing security-class words for bonds, ISINs resolve to legal entities, and drug lookups return RxCUI plus ingredient and brand. The value-parameter guidance is materially richer than 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 user utterances and states explicitly that the tool resolves user-spoken names to canonical/official identifiers required by other tools. It differentiates itself from siblings like entity_profile or compare_entities by framing itself as the identity-lookup step.

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 trigger: 'Use FIRST whenever you have a name but need an ID.' It also enumerates supported entity types and provides example queries. It does not name sibling alternatives or state when not to use it, but the usage context is unmistakable.

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

A3.9/5.0
Disambiguation2/5

Several tool clusters have fuzzy boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer questions through the same routing layer, while polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and bet_research all address prediction-market edges. Even with detailed descriptions, an agent can easily select the wrong variant.

Naming Consistency3/5

Names are uniformly lowercase snake_case and many follow a verb_noun pattern (list_jobs, search_jobs, resolve_entity, validate_claim), but there are numerous noun-first and adjective-first exceptions (entity_profile, recent_alerts, pipeworx_trending, polymarket_arbitrage) plus bare verbs (remember, forget, recall, subscribe). The pattern is readable but not consistently applied.

Tool Count2/5

34 tools is well above the well-scoped range, and the vast majority are not about the server's RemoteOK namesake. The set appears to merge several distinct domains (Pipeworx data research, Polymarket betting, RemoteOK jobs, memory utilities) into one oversized surface, making it feel more like a bundled platform than a focused server.

Completeness4/5

For the dominant Pipeworx/data-research theme, coverage is strong: question answering, grounded verification, entity profiles, comparisons, change feeds, discovery, memory, subscriptions, and citation-based research are all present. The RemoteOK job subset covers list/search/get without obvious dead ends. Minor gaps exist (no direct citation-URI fetcher, no job alert subscriptions), but agents can work around them.

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