Skip to main content
Glama

resolve_person

Resolve person identities to canonical AnchorIDs using email, name, company domain, or external identifiers. Returns match status, confidence scores, and candidate details to verify and link customer records across systems.

Instructions

Resolve a person to an AnchorID using email, name, company domain, or external identifiers (Slack/Google user IDs). Returns status (resolved | needs_review | not_found), confidence score, the canonical AnchorID, match reasons, and any ambiguous candidates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoPerson's email address
nameNoPerson's full name
company_entity_idNoResolved company AnchorID (UUID) for name+company matching
company_domainNoCompany domain for name+company matching
identifiersNoExternal system identifiers
min_confidenceNoMinimum confidence threshold (0-1)
Behavior4/5

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

With no annotations provided, the description carries full behavioral disclosure burden. It excellently compensates by detailing the tri-state status values (resolved | needs_review | not_found), confidence scoring, and ambiguous candidate handling. It implies a read-only lookup operation through the 'Returns...' phrasing, though explicit safety characteristics (idempotent, non-destructive) are not stated.

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?

Two sentences with zero waste: first sentence covers inputs and action, second covers outputs. Information density is high with no filler. The structure front-loads the core verb and resource.

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?

Given the lack of output schema, the description effectively documents return values (status, confidence, AnchorID, candidates). With 6 optional parameters and nested objects, it adequately covers complexity. Minor gap: does not mention that all parameters are optional or provide input combination logic (e.g., minimum required fields).

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

Parameters3/5

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

Schema description coverage is 100%, establishing a baseline of 3. The description adds value by grouping parameters into functional categories (email/name/domain/external identifiers), implying they are alternative resolution methods. However, it does not explain parameter relationships (e.g., that company_entity_id requires name) or validation rules beyond the schema.

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 core action (resolve to AnchorID) and target resource (person). It distinguishes from resolve_company by specifying person-specific inputs like Slack/Google IDs. However, it fails to explicitly differentiate from the sibling resolve_person_batch tool (e.g., 'for single person resolution').

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lists available input methods but provides no guidance on when to use which (e.g., email vs. name+company domain) or when to prefer this over resolve_person_batch. There are no prerequisites or exclusion criteria mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/nolenation04/anchord-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server