// HR & Recruiting

Job Search Next-Step Planner

Name: Job Search Next-Step Planner
Brand: JustHandled Labs
Price: 9 USD
Availability: InStock

Organize your applications, document versions and next actions in a portable local workspace, with cautious follow-up drafts you can review yourself.

Get it on Agensi — $9 Find another skill $9 one-time

Format: Agent skill, not a browser app. You need an AI agent that can load its instructions and use the required tools.

Package requirements: Python CLI on Windows tested; standard-library Python 3.10+ source. Agent-host installation not independently tested.

You get: An application board, document and submission history, next-action plan and reviewable follow-up drafts.

Licence and purchase details

JustHandled Labs paid skill license; included LICENSE.txt governs

Review the offer and access method at your chosen marketplace. Agensi provides connected-agent access, not a download. Buying a skill does not include an AI-agent subscription or setup service.

Agensi access: This product’s bundled-script workflow through Agensi has not been verified here. Tests of other products do not establish this package’s compatibility. Local setup examples apply to separately obtained downloadable packages.

See tested hosts, versions and workflow limits.

Your first useful result

The terminal steps below require a separately obtained complete download. For Agensi, ask your connected agent to check supporting-file access and Python availability first; this product’s Agensi execution has not been verified here. Do not assume the local walkthrough runs in every host.

See which application needs preparation, which needs a date, and which has a follow-up draft to review.

Downloaded package: run the included example

Prepare. Extract the complete package and use Python 3.10 or newer. Run the included fictional practice packet from the package folder. It uses a fixed example date, not today’s date. Choose a fresh output folder whose parent already exists.

Run from the package folder.

python scripts/run.py fixtures/practice.json --output first-search-plan

Review the output. Open today-plan.md and application-board.csv. The fictional Library application retains “resume-v3 + cover-v2” and points to an unsent follow-up draft backed by a supplied submission record. The Clinic application stays in preparation, with its materials missing and next date left for the person to choose. submission-history.csv keeps the supplied history; followup-drafts.json labels the message DRAFT_NOT_SENT.

This is a local planning record, not an inbox connection or an automatic application service. A supplied confirmation is not independently authenticated. Silence is not rejection. Contact restrictions, closed roles and previous follow-ups should suppress duplicate drafts. Your agent host may process prompts remotely; use only information you permit.

Included fictional two-application packet tested on Windows Python 3.12.14; eight package tests passed. Output was REVIEW, with missing material/date questions retained. No application or message was sent, and automatic agent-host installation was not tested.

Ask your agent to prepare the input

Read SKILL.md and references/input-contract.md. Help organize my saved roles, document versions and supplied application confirmations. Ask me to choose review dates consistent with employer instructions. Create a new local plan and board, preserve the earlier packet, and show any missing evidence. Draft a follow-up only where permitted and supported; never send it or assume an application was submitted or an employer replied.

What problem does Job Search Next-Step Planner solve?

Organize your applications, document versions and next actions in a portable local workspace, with cautious follow-up drafts you can review yourself.

Use it to

For an individual managing applications, return a portable next-step plan tied to their material versions and submission evidence; suppress unsafe repeat follow-ups without sending anything.
Prepare your next application or practice session using your own approved facts.
Return to a saved packet without losing earlier work.

What it returns

application-board.csv
findings.csv
followup-drafts.json
manifest.json
report.md
submission-history.csv
summary.json
today-plan.md

A representative input and result

fixture-backed sample

input {
  "as_of": "2026-09-09T12:00:00Z",
  "applications": [
    {
      "id": "a1",
      "company": "Example Library",
      "role": "Support assistant",
      "job_reference": "LIB-7",
      "stage": "applied",
      "do_not_contact": false,
      "allow_followup": true,
      "material_version": "resume-v3 + cover-v2",
      "next_at": "2026-09-09T10:00:00Z"
    },
    {
      "id": "a2",
      "company": "Example Clinic",
      "role": "Receptionist",
      "job_reference": "CL-4",
      "stage": "drafting",
      "do_not_contact": false,
      "allow_followup": false,
      "material_version": "",
      "next_at": null
    }
  ],
  "events": [
    {
      "id": "e1",
      "application_id": "a1",
      "kind": "submitted",
      "at": "2026-09-02T12:00:00Z",
      "source": "confirmation:example-1"
    }
  ]
}

result # Your next steps

## Example Library  —  Support assistant

Review a follow-up draft against the employer instructions.

Your next date: 2026-09-09T10:00:00Z
Materials: resume-v3 + cover-v2

## Example Clinic  —  Receptionist

Prepare your role-specific resume and cover letter; review them before submitting.

Your next date: choose one
Materials: not recorded

Access and approval boundaries

Read one local input JSON file.
Write a new local output directory; no network or external actions.

Known limitations

Manual normalized JSON inputs; no browser clipper, live inbox connection or persistent hosted dashboard.
Submission records do not prove delivery or employer response.
Next dates are the user’s choices; existing ambiguous contact events suppress another draft.

Questions

What do I receive?

A downloadable skill with a local Python helper, input contract, synthetic fixtures, tests and sample reports.

What do I need to run it?

Python 3.10 or newer and your authorized normalized JSON records. The helper uses the standard library; Windows CLI execution was tested.

Does it connect to my HR software?

No. You supply a local export normalized to the documented schema. There is no ATS or HRIS integration.

Will it apply, contact employers or judge my suitability?

No. It helps you prepare your own materials or practice. It never sends or submits, infers sensitive traits or predicts job outcomes.

What does READY mean?

No encoded finding in the supplied scope. It does not prove source truth, comprehensive readiness, legal compliance or approval to act.

What are the main limits?

Manual normalized JSON inputs; no browser clipper, live inbox connection or persistent hosted dashboard.

Where does my data go?

Processing location depends on your access route. A downloaded Python helper runs where you execute it; an agent-hosted run uses that host’s environment and privacy settings. Start with fictional data and authorize any processing of real personal or workplace information.