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auram-stone

Feather MCP Server

by auram-stone

list_contacts

Fetch Feather Messenger CRM contacts with optional filters for tag, label, or search. Enables AI agents to access lead data for targeted outreach and contact management.

Instructions

List Feather Messenger CRM contacts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoFilter by tag
labelNoFilter by label
limitNoMaximum number of contacts to return
searchNoSearch by name or tag

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYesTotal contacts matching filters
contactsYesContacts list
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavior. It only says 'List' without elaborating on defaults, pagination limits, whether it returns all contacts or only filtered, or any side effects. This is a significant lack of transparency for a data-retrieval tool.

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 a single sentence and front-loaded, which is concise. However, it is under-specified: it omits critical information about filters and usage context, making it appear minimal rather than appropriately concise.

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

Completeness2/5

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

Despite having an output schema and full parameter coverage, the description lacks essential context such as the tool's filtering options, relationship to sibling tools, or expected behavior. For a tool with 4 optional parameters, the description is too sparse to be considered complete.

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 covers 100% of parameters (tag, label, limit, search) with descriptions, so the baseline is 3. The description itself adds no additional parameter semantics; it doesn't mention filtering capabilities or how parameters interact.

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 action (list) and resource (Feather Messenger CRM contacts), making the core purpose unambiguous. However, it does not distinguish this tool from siblings like search_leads, which may also list or search contacts, so it lacks sibling differentiation.

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 guidance on when to use this tool versus alternatives. There is no mention of use cases, exclusions, or comparison with sibling tools like search_leads or get_crm_stats, leaving the agent without context for selection.

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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