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list_applications

Retrieve and filter job applications in a campaign by status, tags, role, employment type, or text to review and manage your job search.

Instructions

List applications with optional status, tags, role, employment type, and text filters

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoAND-combined tag filter
filterNoGeneral-purpose text filter (case-insensitive)
statusNoFilter by application status
campaignYesCampaign name (e.g. "default")
targetRoleNoFilter by target role slug
employmentTypeNoFilter by employment type

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It never states ordering, pagination, result limits, or whether an empty filter set returns all applications, and it does not disclose that the required campaign scopes the result set. Only the read-only nature is inferable from 'List'.

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?

A single front-loaded sentence that names the operation first and the filter dimensions after. It is efficient, though the terse phrasing leaves no room for the behavioral context the rest of the definition lacks.

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?

With no annotations and no output schema, the description is the only place behavioral context could live, yet it omits pagination, ordering, default result scope, and the significance of the required campaign parameter. For a six-parameter list tool this is notably thin.

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 coverage is 100%, so the enum values, tag AND-combination, and case-insensitive filter behavior are already documented in the schema. The description's filter list largely restates the schema and adds no syntax or format detail beyond it, which matches the baseline 3.

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?

States a clear verb+resource ('List applications') and enumerates the filter dimensions, so the agent knows this is a filtered read of applications rather than interviews or campaigns. It does not explicitly differentiate itself from siblings like show_application or list_interviews, but the resource is unambiguous.

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?

No guidance on when to use this versus show_application, list_interviews, or get_stats, and no prerequisites (such as the required campaign being in scope) are mentioned. The enumerated filters imply a search use case, but nothing tells the agent when this is the right choice.

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