// HR & Recruiting

Employee Onboarding Readiness Reconciler

Name: Employee Onboarding Readiness Reconciler
Brand: JustHandled Labs
Price: 19 USD
Availability: InStock

Reconcile day-one onboarding tasks, ownership, deadlines, completion evidence and dependencies across supplied HR, IT and manager exports.

Get it on Agensi — $19 Find another skill $19 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 evidence ledger, dependency gaps, ownership and deadline findings, and a readiness summary.

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.

What problem does Employee Onboarding Readiness Reconciler solve?

Reconcile day-one onboarding tasks, ownership, deadlines, completion evidence and dependencies across supplied HR, IT and manager exports.

Use it to

For an HR/IT owner reviewing day-one handoffs, compare exported task dependencies and completion locators; unlike broad induction drafting, expose unsupported completion and dependency cycles with reproducible failure codes.
Review a synthetic example before supplying authorized records.
Repeat the review after owners resolve source gaps.

What it returns

evidence-ledger.csv
findings.csv
manifest.json
missing-dependencies.csv
ownership-and-deadline-gaps.csv
readiness-summary.json

A representative input and result

fixture-backed sample

input {
  "subject_id": "hire-001",
  "as_of": "2026-09-09T12:00:00Z",
  "start_at": "2026-09-10T09:00:00-05:00",
  "start_records": [
    {
      "id": "HR",
      "start_at": "2026-09-09T12:00:00Z"
    }
  ],
  "tasks": [
    {
      "id": "laptop",
      "owner": "",
      "required": true,
      "status": "pending",
      "due_at": "2026-09-08T12:00:00Z",
      "depends_on": [],
      "evidence": ""
    },
    {
      "id": "access",
      "owner": "IT",
      "required": true,
      "status": "complete",
      "due_at": "2026-09-08T12:00:00Z",
      "depends_on": [
        "laptop"
      ],
      "evidence": ""
    }
  ]
}

result # Employee onboarding readiness

NOT READY — HUMAN REVIEW REQUIRED

Supplied records only; human review required. Not an employment decision.

- START_DATE_CONFLICT [HR]: Supplied start date differs from declared start.
- OVERDUE [access]: Deadline passed with no supported completion.
- REQUIRED_INCOMPLETE [access]: Required work is not evidenced complete.
- UNMET_DEPENDENCY [access]: Prerequisite laptop is not evidenced complete.
- UNSUPPORTED_COMPLETION [access]: Completion claim has no source locator.
- MISSING_OWNER [laptop]: Assign accountable owner.
- OVERDUE [laptop]: Deadline passed with no supported completion.
- REQUIRED_INCOMPLETE [laptop]: Required work is not evidenced complete.

Access and approval boundaries

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

Known limitations

Evidence presence is not authenticity, freshness or export completeness.
No live HRIS connection or access provisioning.
All dates require ISO timestamps with offsets; dependency cycles are invalid.

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.

Can it make decisions or contact people?

No. It produces local reports for human review. It never ranks applicants, sends messages or changes accounts.

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?

Evidence presence is not authenticity, freshness or export completeness.

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.