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juanzjck

jobfinder-mcp

by juanzjck

add_job

Add a job found on LinkedIn, via referral, or email to your tracker with full details, including description, salary, and notes.

Instructions

Add a job you found elsewhere (LinkedIn, a referral, an email) to the tracker.

Use this to paste a full job description for a listing that did not come from search_jobs. Reusing an existing job_id overwrites that listing's fields while keeping its application status.

Args: title: role title. company: hiring company. description: full job description text. location: e.g. "Remote", "Berlin". url: link to the original posting. salary: free-form, e.g. "$150,000 - $180,000". tags: comma-separated, e.g. "python, backend". notes: your own notes about the role. job_id: optional explicit id; defaults to a generated "manual:" id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
tagsNo
notesNo
titleYes
job_idNo
salaryNo
companyYes
locationNo
descriptionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden and does disclose a key behavioral trait: overwriting existing job_id fields while preserving application status, and default ID generation as 'manual:<slug>'. It could add return/error behavior but covers the main side effect.

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 well-structured with a clear opening purpose, followed by a concise usage note and an organized Args list. Every sentence adds value and nothing is redundant.

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

Completeness5/5

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

Despite having 9 parameters and no schema descriptions, the description provides complete context: usage scenarios, parameter meanings, ID behavior, and overwrite semantics. An output schema exists, so not explaining return values is acceptable. It is fully sufficient for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description includes a detailed Args section explaining all 9 parameters with examples (e.g., 'Remote', '$150,000 - $180,000', 'python, backend'), fully compensating for the schema's lack of descriptions.

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 identifies the specific verb (add), resource (job), and key context (found elsewhere, not from search_jobs), distinguishing it from sibling tools like search_jobs and save_job.

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

Usage Guidelines5/5

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

Explicitly states 'Use this to paste a full job description for a listing that did not come from search_jobs' and describes the behavior of reusing an existing job_id (overwrite fields while keeping status), giving clear when-to-use vs alternative guidance.

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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