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Glama

contact_update

Update contact fields

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
genderNoGender
statusNoContact status
companyNoCompany
industryNoIndustry
nicknameNoNickname
pronounsNoPronouns
job_titleNoJob title
last_nameNoLast name
avatar_urlNoAvatar URL
contact_idYesThe contact ID to update
first_nameNoFirst name
work_notesNoWork notes
is_favoriteNoMark as favorite
maiden_nameNoMaiden name
met_at_dateNoDate you met this person
middle_nameNoMiddle name
birthday_dayNoBirthday day (1-31)
birthday_dateNoFull birthday date (YYYY-MM-DD)
birthday_modeNoBirthday mode
deceased_dateNoDate of death (YYYY-MM-DD)
birthday_monthNoBirthday month (1-12)
met_at_locationNoWhere you met this person
met_descriptionNoHow you met
met_through_contact_idNoContact ID of person who introduced you
birthday_year_approximateNoApproximate birth year

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / middle_name
      Added value: +{
      +  "description": "Middle name",
      +  "type": "string"
      +}
  2. First observed

TDQS

C2.8/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it reveals nothing beyond a basic mutation operation. It does not explain whether updates are partial or full, what happens if the contact doesn't exist, or any permission requirements. The description essentially restates the tool name.

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 a single efficient sentence with no wasted words. It is front-loaded and easy to parse. However, it is also extremely sparse, which slightly reduces the score from a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (25 parameters, 1 required, no output schema) and complete lack of usage or behavioral context, the description is grossly insufficient. It does not help the agent understand how to use the tool correctly, such as which fields to provide, whether updates are additive, or how errors are reported.

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?

The input schema has 100% property description coverage, so the schema already documents all parameters. The description adds no additional parameter context or relationships, so it earns the baseline of 3. It neither helps nor hurts beyond the schema.

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 'Update contact fields' uses a specific verb ('update') and resource ('contact fields'), clearly distinguishing it from sibling tools like contact_create, contact_get, and contact_delete. It unambiguously states the tool's function.

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 gives no explicit guidance on when to use this tool vs alternatives. It does not mention that contact_id is required, or that this tool is only for modifying existing contacts, nor does it reference any other tools. Usage context is only implied by the verb 'update'.

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
Disambiguation4/5

Most tools are clearly distinct by entity, but contact_get and contact_timeline overlap significantly, and debt_manage's action='list' duplicates what other entities do with a dedicated list tool. Descriptions are detailed enough to resolve most ambiguity, though.

Naming Consistency3/5

Tool names are mostly snake_case and readable, but they mix conventions: noun_verb (contact_create), verb_noun (batch_create_activities), and descriptive phrases (contacts_needing_attention). The noun_manage pattern is dominant, but the lack of uniformity makes the naming less predictable.

Tool Count2/5

With 42 tools, the surface is very large, even for a full-featured CRM. Many tools bundle multiple actions, but the sheer number forces an agent to consider many options, increasing selection difficulty and cognitive load.

Completeness5/5

The server provides comprehensive CRM coverage: contacts, activities, notes, tasks, reminders, gifts, debts, relationships, tags, custom fields, notifications, settings, and exports. It supports batch operations, duplicate detection, merge, and special queries, leaving few if any obvious gaps.