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Glama

Outlook Contacts

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. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which already signal safe operations. The description goes well beyond that, disclosing internal cascading through multiple endpoints, graceful degradation of LEI/FIGI when sources are unavailable, the behavior when multiple matches occur (returns figi_candidates), and that unresolved identifiers are explicitly listed under `unresolved`. It also notes source labeling for each identifier. This is rich behavioral context that the annotations do not provide.

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, but it is densely packed with instructional content, covering two entity types, multiple data sources, edge cases, and failure modes. It is front-loaded with the core purpose and the 'Use FIRST' directive. While it could be pruned slightly, every sentence earns its place; the length is acceptable for the tool's complexity. It is not bloated or redundant.

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 has two distinct modes, multiple external sources (EDGAR, GLEIF, OpenFIGI, RxNorm), and a no-output-schema environment, the description is exceptionally complete. It covers what each type returns, how ambiguous names are handled, what happens when sources fail, and even mentions the citation format (pipeworx://rxnorm/concept/...). There are no significant gaps an agent would need to guess about.

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?

With 100% schema description coverage, the schema already documents both parameters. The description adds substantial value: it explains the exact input format (e.g., for bonds use issuer name exactly as printed, never the full noun phrase), gives examples for both types (AAPL, 0000320193, 'ozempic'), and clarifies that for drugs it returns RxCUI plus brand. It even warns about trailing words that break FIGI lookup. This goes far beyond the schema's basic type description.

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 the core purpose very specifically: "resolve a user-spoken NAME to the canonical/official identifiers other tools require as input." It enumerates query patterns (ticker, CIK, LEI, RxCUI) and supported entity types (company, drug) with concrete examples. It clearly distinguishes itself from siblings by focusing on name-to-identifier resolution, even noting that 'using resolve_entity replaces 2-3 manual lookups'.

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 gives explicit guidance: 'Use FIRST whenever you have a name but need an ID.' It also explains when NOT to use it—when a name maps to multiple instruments, it returns candidates rather than asserting one—and provides detailed instructions for each type (e.g., 'Pass the ENTITY NAME ONLY'). It even warns against including trailing security-class words. This is far more than vague context; it is actionable selection advice.

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

A3.6/5.0
Disambiguation2/5

Several tools are near-duplicates by name and function, notably ask_pipeworx vs ask_pipeworx_beta, and the dense Polymarket family (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). Long descriptions help, but an agent cannot reliably pick between these without reading closely.

Naming Consistency4/5

Almost all names are lowercase_snake_case and mostly verb-leading (discover_tools, resolve_entity, unsubscribe), but there are noun-first exceptions (entity_profile, recent_changes, pipework_trending) and several phrasal or compound forms. This is a minor deviation from a clean verb_noun pattern rather than a chaotic mix.

Tool Count2/5

31 tools is over the heavy threshold, and the set feels bloated: multiple query routers, a half-dozen overlapping Polymarket tools, and two AI-visibility probes that could be merged. The count is especially hard to justify for a server named Tools 'OutLook Contacts', since none are contact management.

Completeness1/5

For the server's stated domain, Outlook Contacts, there are zero tools in that domain — no create contact, no list contacts, no update, no delete, no folders or mailboxes. Even though the actual Pipework toolkit is broad for its own domain, this set fails its declared intend domain entirely.

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