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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

A4.7/5.0
Behavior5/5

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

The description discloses behavioral traits beyond the annotations: graceful degradation when GLEIF/OpenFIGI is unavailable, ambiguous matches returning figi_candidates without asserting, unresolved identifiers being explicitly listed, and internal cascading of lookups. These details add context that readOnlyHint/openWorldHint/idempotentHint do not cover.

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 long and dense, but every sentence carries relevant information and the usage guidance is front-loaded. However, the wall-of-text structure with nested parentheses and long asides makes parsing harder than necessary, so it does not fully earn a 5.

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?

With no output schema, the description fully covers return values (CIK, ticker, LEI, ownership, FIGI, RxCUI, citation) and edge cases (ambiguous matches, unresolved identifiers, non-US issuers, non-equity instruments, enrichment failures). No significant gap remains for an agent to know how to call and interpret the result.

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 semantics for the `value` parameter, warning against full noun phrases and instructing to pass the issuer exactly as printed. It also explains accepted formats (ticker, CIK, ISIN, names) and what the `type` parameter controls, far surpassing schema basics.

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 states a specific purpose: resolving a user-spoken name to canonical/official identifiers, with concrete query examples. It clearly distinguishes itself from sibling tools by framing the output as IDs that 'other tools require as input' and supports two explicit entity types.

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 explicitly instructs 'Use FIRST whenever you have a name but need an ID,' providing an actionable condition. It does not name alternative sibling tools or list exclusion cases, but the directive is strong and covers the primary scenario.

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

A3.8/5.0
Disambiguation4/5

Most tools target distinct purposes (e.g., ask_pipeworx vs. get_repo vs. validate_claim), but there is some overlap between ask_pipeworx and ask_pipeworx_grounded, and between bet_research and polymarket_edges. Overall, an agent can generally distinguish them.

Naming Consistency2/5

Tool names lack a consistent pattern: some are verb_noun (search_repos, get_user), others are noun_verb (entity_profile), and many are compound descriptor phrases (polymarket_arbitrage, scan_dependency). This mixed convention makes the set feel disjointed.

Tool Count2/5

38 tools is excessive for a server named 'Github', especially since many tools (e.g., ai_visibility_check, bet_research) are unrelated to GitHub functionality. The count would be appropriate for a broader 'Pipeworx' server but not for a focused GitHub server.

Completeness2/5

The GitHub-relevant tools are limited to read-only operations (get_repo, list_commits, etc.), lacking essential actions like creating/updating repos, issues, or pull requests. The inclusion of numerous non-GitHub tools does not compensate for these gaps.

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