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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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / value / description
      Previous value: -"For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., \"ozempic\", \"metformin\")."New value: +"For 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."
  2. Changed3 schema fields changed
    • changedInput schema / properties / type / description
      Previous value: -"Entity type. v1 supports \"company\"."New value: +"Entity type: \"company\" or \"drug\"."
    • changedInput schema / properties / type / enum
      Previous value: -[
-  "company"
-]New value: +[
+  "company",
+  "drug"
+]
    • changedInput schema / properties / value / description
      Previous value: -"Ticker, CIK, or company name (e.g., \"AAPL\", \"0000320193\", \"Apple\")."New value: +"For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., \"ozempic\", \"metformin\")."
  3. Added

TDQS

A4.6/5.0
Behavior5/5

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

The annotations already cover read-only, idempotent, open-world, and non-destructive traits, so the bar shifts to extra behavioral context. The description adds substantial behavior: internal cascading through multiple endpoints, graceful degradation when GLEIF/OpenFIGI are unavailable, ambiguous-name handling via figi_candidates, explicit unresolved fields, and source labelling of every identifier. This goes far beyond the structured annotations.

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 text is dense and heavily parenthetical, but nearly every sentence contributes operational guidance. It front-loads the most common use-case pattern and iterates from main purpose to type specifics to failure behavior. A bit of pruning and structural formatting would improve readability, but the length is largely justified by the multi-endpoint complexity.

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 must convey what callers receive and how edge cases behave. It does: canonical identifiers per type, source labels, figi_candidates for ambiguous instrument matches, unresolved entries, the ISIN-to-LEI fallback path, and enrichment degradation behavior. An agent has enough context to invoke the tool correctly and interpret unusual results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds genuinely useful disambiguation beyond the schema, especially the 'ENTITY NAME ONLY' rule, the bond-issuer caveat, and the note that trailing security-class words will fail FIGI matching. It reinforces ticker/CIK/name input forms with examples, making parameter usage significantly safer.

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 ('What's the ticker for…', 'find the CIK for…'), then states the specific job: resolve a user-spoken name to canonical identifiers other tools require as inputs. It further enumerates supported types and identifier sources, making the tool's purpose unmistakable and distinct from generic lookup tools.

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?

The description gives an explicit trigger rule — 'Use FIRST whenever you have a name but need an ID' — and provides type-specific guidance including input forms and a sharp caveat about passing only the issuer name for bonds. It does not explicitly contrast itself with sibling entity tools such as entity_profile or compare_entities, so a small gap remains in when-not-to-use 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

A3.8/5.0
Disambiguation4/5

Descriptions are exceptionally detailed and differentiate tools well; the ask_pipeworx family (stable/beta/grounded), polymarket tools, and npm lookup tools each have clear separation of intent. Minor overlap exists between polymarket_edges and polymarket_arbitrage (both surface opportunities) and between discover_tools, suggest_questions, and pipeworx_trending (all aid discovery), but descriptions mostly resolve the ambiguity.

Naming Consistency3/5

All names are snake_case and several families are consistent (get_*, list_*, search_*, ask_pipeworx, polymarket_*), but the convention is inconsistent: verb-first names (resolve_entity, validate_claim, scan_dependency) coexist with noun-first or noun-only names (entity_profile, deep_research, bet_research, recent_alerts, ai_visibility_check, pipeworx_trending, polymarket_arbitrage). No clear governing pattern beyond snake_case.

Tool Count2/5

36 tools is well over the 25-tool heavy threshold, and the majority (~29) are unrelated to the server's declared 'npm' identity — they are Pipeworx data-query, prediction-market, memory, and subscription tools. Only about 7 tools (search_packages, get_package, get_version_info, list_versions, get_downloads, scan_dependency, generate_llms_txt) actually pertain to npm. The scope is a kitchen-sink mismatch with the server name.

Completeness3/5

For npm, the read-side surface is reasonably complete: search, inspect package metadata, version listings, download counts, and a dependency-safety composite check. However, there are no lifecycle operations (publish, unpublish, deprecate, set versions/tags), leaving a notable gap, and the bulk of the server's functionality (data queries, prediction bets) belongs to an entirely different domain that can't be cohesively evaluated against the npm purpose.

Resources