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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

A5/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, but the description adds substantial context beyond these: graceful degradation if GLEIF/OpenFIGI is unavailable, explicit `unresolved` reporting, multi-match behavior returning `figi_candidates`, and source-labelled identifiers. No contradiction with annotations exists.

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 densely packed with non-redundant, decision-relevant detail, and it is front-loaded with trigger phrases and the primary usage directive. Each parenthetical and clause adds either a behavioral edge case, a fallback behavior, or an explicit input constraint, so it earns its length for a complex multi-source tool.

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 the tool's complexity (two entity types, multiple identifier systems, optional enrichment sources, fallback behavior) and the absence of an output schema, the description covers all critical call-time knowledge: accepted inputs, resolution scope, candidate ambiguity behavior, unresolved-id behavior, and degradation semantics. An agent can confidently select and invoke this tool without further context.

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 critical semantics beyond the schema. It explains what each type means, supplies examples for both company and drug values, and gives a nuanced rule for bond lookups: pass only the issuer name, because trailing security-class words will fail the FIGI match. This materially improves successful invocation.

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 begins with concrete natural-language triggers ("What's the ticker for…", "find the CIK for…") and immediately states the core function: resolving a user-spoken name to canonical identifiers. It specifies the supported entity types (company, drug) and the identifier sets each resolves to, clearly distinguishing it from sibling profile/compare tools by framing the output as inputs other tools require.

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?

The description includes an explicit directive: "Use FIRST whenever you have a name but need an ID." It further clarifies when it is not appropriate by warning that for bonds the user must pass the issuer exactly as printed and never the full noun phrase, and it explains that the tool replaces 2-3 manual lookups, giving an agent a strong decision rule.

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

B3.4/5.0
Disambiguation2/5

The set is dominated by near-overlapping research tools: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions with heavily overlapping descriptions, and the six polymarket_* tools plus bet_research form a second confused cluster. The five confluence_* tools are distinct, but an agent would struggle to pick among the research/betting alternatives without reading thousands of words of caveats.

Naming Consistency2/5

Most names are snake_case, but the conventions are mixed: verb_noun (confluence_create_page, validate_claim), noun_verb (bet_research), prefixed nouns (polymarket_arbitrage, pipeworx_feedback), and bare verbs (recall, forget). The glaring issue is that the server is named Confluence yet only 5 of 36 tools carry the confluence_ prefix, leaving the other 31 tools with no thematic prefix and no consistent pattern.

Tool Count2/5

36 tools is already in the 'too many' range, but the mismatch is deeper: only 5 tools relate to Confluence while 31 tools cover an entirely different domain (Pipeworx data research, prediction markets, subscriptions). For a wiki server this is wildly over-scoped; as a combined surface it is bloated and lacks a unifying purpose.

Completeness2/5

For the Confluence domain the surface is incomplete: pages can be created, fetched, listed, and searched, but there is no update_page, delete_page, comment, attachment, or content-type coverage, leaving obvious CRUD dead ends. For the Pipeworx domain, coverage is broad but disorganized, with overlapping research paths and no clear hierarchy.

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