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pokemon

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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description goes far beyond these by disclosing multi-source cascading lookups, graceful degradation when GLEIF/OpenFIGI is unavailable, explicit `unresolved` reporting instead of omission, and the `figi_candidates` behavior when a name matches multiple instruments. These are high-value behavioral details an agent would not otherwise know.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is information-dense and front-loaded with examples and the primary use instruction, but it becomes sprawling with long parentheticals, nested caveats, and semicolon chains. Most content earns its place, but the structure is harder to parse than it should be for an agent scanning quickly.

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 explain what the tool returns, and it does: canonical identifiers, source labels, unresolved identifiers, and `figi_candidates`. It also covers edge cases like non-US issuers, non-equity instruments, multiple matches, and enrichment failures. The tool is more than adequately specified for correct invocation.

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?

Schema coverage is 100%, but the description adds substantial meaning beyond the schema: accepted input forms for `value`, examples like 'AAPL' and 'CH0038863350', the ISIN-to-LEI mapping, the warning to pass the issuer name exactly as printed and never the full noun phrase, and the distinction between brand and generic drug names. This directly prevents common invocation mistakes.

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 action — resolving a user-spoken name to canonical/official identifiers — and names the exact resources ('company', 'drug') with their identifier systems (CIK, ticker, LEI, FIGI, RxCUI). It is clearly differentiated from siblings like entity_profile and compare_entities by emphasizing 'other tools require as input' and 'Use FIRST whenever you have a name but need an ID.'

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 explicit routing guidance: 'Use FIRST whenever you have a name but need an ID.' It also defines accepted input forms and entity types. It does not explicitly name alternative tools or state when NOT to use this tool, but the guidance is strong enough for an agent to select it in the intended cases.

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

A3.5/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx, ask_pipeworx_beta (explicitly described as identical), ask_pipeworx_grounded, and deep_research all handle natural-language data queries, while six polymarket_* tools cover prediction-market analysis with blurry boundaries. The four legitimate Pokemon tools are drowned out by dozens of unrelated Pipeworx utilities, making tool selection confusing.

Naming Consistency2/5

Tool names mix verb_noun (get_pokemon, ask_pipeworx), noun phrases (entity_profile, recent_changes), and bare verbs (forget, recall, subscribe) with no consistent pattern. Even the Pipeworx-related tools alternate between ask_pipeworx*, pipeworx_*, polymarket_*, and descriptive names, so the naming is a hodgepodge rather than a predictable system.

Tool Count2/5

At 35 tools, this exceeds the 25+ threshold for a coherent toolkit. The 'pokemon' server name implies a small, domain-specific set, yet 31 of the tools are unrelated Pipeworx data-research, prediction-market, and memory utilities, making the count wildly inappropriate for the apparent purpose.

Completeness2/5

For a Pokemon domain, the surface is skeletal: only get_pokemon, get_ability, get_type, and get_evolution_chain exist, with no moves, items, locations, or search/list capabilities. The extensive Pipeworx tools clearly belong to a different server altogether, creating a massive coherence gap for the stated 'pokemon' purpose.

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