jobctl

Update application

update_application

Update fields of an application (get the id from list_applications). Status changes are logged to the timeline automatically. Example: update_application({id: "…", status: "interview", next_action: "prepare system design", next_action_due: "2026-07-20"}).

Input Schema

TableJSON Schema

Name	Required	Description
`id`	Yes
`url`	No	Link to the job posting
`role`	No
`remote`	No
`source`	No	LinkedIn, referral, recruiter, Easy Apply…
`status`	No
`company`	No
`location`	No
`priority`	No	A = top priority
`applied_at`	No	ISO date YYYY-MM-DD
`cv_variant`	No	Which CV was sent: DE, EN, AI-focused…
`match_notes`	No	Markdown match assessment: why the candidate fits this role — strengths vs requirements, gaps, level/salary advice, process notes. Save your vacancy analysis here so it is not lost; shown as an expandable section in the dashboard.
`next_action`	No	e.g. "follow-up", "thank-you email"
`remote_note`	No	e.g. "2 days office"
`salary_asked`	No	What the candidate asked for — yearly gross EUR as a plain number, e.g. 110000
`salary_range`	No	Posting salary range upper bound — yearly gross EUR, plain number
`next_action_due`	No	ISO date YYYY-MM-DD
`salary_range_min`	No	Posting salary range lower bound — yearly gross EUR, plain number
`next_interview_at`	No	ISO datetime, e.g. 2026-07-20T14:00:00+02:00

TDQS

A4.2/5.0

Behavior4/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false. The description adds that 'Status changes are logged to the timeline automatically', which is a behavioral trait beyond the annotations. It does not mention other side effects, but the added context is valuable.

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?

The description is a single sentence plus an example, with no verbosity. Every word is functional, and the key information is front-loaded.

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 tool has 19 parameters and no output schema, the description covers the essential behavior (updates fields, logs status changes) and provides a working example. It does not explain return values or error handling, but the context is sufficient for a mutation tool.

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 68%, meaning many parameters already have descriptions. The description adds guidance with an example and notes that match_notes should be saved 'here so it is not lost'. This adds value but does not fully compensate for the remaining undocumented parameters.

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 clearly states the verb 'Update' and the resource 'application', and distinguishes it from siblings like list_applications by specifying how to get the id. The example reinforces the purpose.

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

Usage Guidelines4/5

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

The description provides a prerequisite ('get the id from list_applications') and implicitly contrasts with add_application and list_applications. It does not explicitly state when not to use it, but the context is clear enough.

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

A4.4/5.0

Disambiguation5/5

Every tool targets a distinct resource and action: application, note, analysis attachment, file attachment, interview file, application detail, due actions, planned schedule, application listing, interview logging, and application updates. Even the three 'attach' tools are clearly differentiated by purpose (analysis vs CV/cover letter vs interview prep). The only potential overlap between get_due and get_planned is explicitly resolved in the descriptions.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (add_application, get_application, list_applications, update_application, attach_analysis, log_interview, etc.). The verb prefix accurately reflects the action, and nouns are singular for single-item operations and plural for list operations, maintaining a predictable convention.

Tool Count5/5

With 11 tools, the server is well-scoped for a job application tracking domain. Each tool covers a necessary function without redundancy, and the count is neither sparse nor overwhelming.

Completeness4/5

The tool set covers the full lifecycle of an application: create, read, list, update, plus notes, attachments, analysis, and interview logging. Minor gaps exist—there is no explicit delete or archive tool (though status updates can archive), and interviews cannot be directly updated or removed after logging—but these are workable within the existing surface.

Resources

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