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add_interview

Log a new interview entry for a job application by specifying campaign, application slug, date/time, type, location, and interviewers.

Instructions

Add a new interview entry for an application

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesApplication slug
typeNoInterview type
whenYesInterview datetime (e.g. "2026-06-15 10:00")
titleNoInterview title
campaignYesCampaign name (e.g. "default")
durationNoDuration in minutes
locationNoInterview location
interviewersNoInterviewer names

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 behavioral burden. 'Add' implies a mutation, but it says nothing about permissions, whether an existing entry is overwritten or rejected, whether the campaign/slug must already exist, or what a successful call returns. For a write tool with zero annotation coverage this is a real gap.

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 tight sentence with the action front-loaded and no filler. It is appropriately sized for the message, though it is arguably too short to count as strongly structured.

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?

For an 8-parameter mutation with no annotations and no output schema, the description should at minimum flag required inputs (campaign, slug, when), the duplicate-handling behavior, and that it operates within a campaign context. None of that is present.

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% across all 8 parameters, including the enum of interview types and the datetime format example, so the schema does the documentation work. The description adds no parameter meaning beyond it, which places this at the baseline.

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 specific verb+resource ('Add a new interview entry') qualified by scope ('for an application'). That is enough to distinguish it from read-side siblings like list_interviews or read_prep, and from mark_interview, though it never names those siblings explicitly.

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?

There is no when-to-use guidance and no mention of alternatives. The toolset contains list_interviews and mark_interview, and nothing here tells an agent which one applies when it wants to record vs. view vs. update interview state.

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