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Google_calendar

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

A4.4/5.0
Behavior5/5

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

Beyond the read-only/idempotent annotations, the description discloses cascading internal lookups, graceful degradation when GLEIF or OpenFIGI are unavailable, ambiguity handling via figi_candidates, explicit unresolved fields, and source-labelled identifiers. This materially enriches what the agent can expect at runtime, and there is no annotation contradiction.

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?

There is no filler and every sentence adds real information, but the company branch is a dense run-on paragraph with deep parentheticals that mix output fields, input forms, ambiguity policy, and failure behavior. The content is appropriately detailed for the tool's complexity, but the structure could be much easier to scan with bullets or shorter sentences.

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?

With no output schema, the description explains return semantics well: unresolved identifiers are stated explicitly, ambiguous FIGI matches return figi_candidates, every identifier is source-labelled, and enrichment can degrade gracefully. It is largely complete for correct invocation, though an explicit example of the returned shape would close the remaining gap.

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 meaning far beyond the schema: value accepts ticker, CIK, ISIN, or company name for company; brand or generic for drug; and it warns against passing trailing security-class terms in bond names. This is critical invocation guidance the schema alone does not provide.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb and resource: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input,' backed by concrete query examples and two supported entity types. It is clear what the tool does, but it does not explicitly name or contrast sibling tools such as entity_profile, so differentiation remains implicit.

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,' plus type-specific guidance and exact input constraints, such as passing the bond issuer name only and avoiding trailing security-class words. However, it does not state when not to use this tool or name alternatives, so exclusions are absent.

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

B3.3/5.0
Disambiguation1/5

The tool set is a mix of 5 Google Calendar tools and 31 unrelated Pipeworx tools (e.g., ask_pipeworx, deep_research, entity_profile). Even within Pipeworx, tools like ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded have highly overlapping purposes, making it very difficult for an agent to distinguish which tool to use.

Naming Consistency1/5

Naming conventions are chaotic. The Google Calendar tools follow a consistent gcal_ prefix, but the rest use various patterns: pipeworx_*, polymarket_*, single words (remember, recall), and others (bet_research, scan_dependency). There is no overarching pattern.

Tool Count1/5

With 36 tools, the count is high, but only 5 are relevant to Google Calendar. The remaining 31 tools are from a completely different domain (Pipeworx data access, Polymarket betting, etc.), making the tool count severely inappropriate for the server's stated purpose.

Completeness2/5

For Google Calendar, the tools provide basic CRUD (create, get, list, search, list_calendars) but lack update and delete functionality. The vast number of unrelated tools does not compensate for these gaps. The overall surface is incomplete for the calendar domain.

Resources