See who confirmed policies and trainings

hr_policy_status · Reads only · Markdown

Who confirmed each policy's current version, and who holds a valid training of each kind.

Free*

*Free up to 1,000,000 reads a month for the whole account, then $0.50 per 10,000 reads.

Who still hasn't confirmed the AI use policy, and who needs AI literacy training?

Your agent callshr_policy_statusFree*

The example business is Hansen & Voss, a restaurant-equipment wholesaler in Hamburg with 60 staff. The reply is the one the tool really gives.

With these arguments

{
  "training_kind": "ai_literacy"
}

What comes back

{
  "policies": [
    {
      "name": "ai-use-policy",
      "title": "How we use AI at Hansen & Voss",
      "version": 1,
      "departments": [
        "Warehouse",
        "Support"
      ],
      "updated_at": "2026-10-14T08:00:00+00:00",
      "people": 3,
      "acknowledged": [],
      "waiting": [
        {
          "person_id": 4103,
          "name": "Jonas Becker"
        },
        {
          "person_id": 4102,
          "name": "Tom Okafor"
        }
      ],
      "not_sent": []
    }
  ],
  "trainings": [
    {
      "kind": "ai_literacy",
      "people": 4,
      "trained": 1,
      "not_trained": [
        {
          "person_id": 4103,
          "name": "Jonas Becker"
        },
        {
          "person_id": 4102,
          "name": "Tom Okafor"
        }
      ],
      "expiring": []
    }
  ]
}

Use it when

An auditor or a manager asks who has read the policies or been trained in AI use.

What it does

Per policy, its current version and who in its scope confirmed it, who has a link waiting and who was never sent one; per kind of training (or one kind), who holds a valid one, who has none and what expires within 60 days. For audits and AI literacy (EU AI Act Art. 4).

What comes back

policies: each with its version and the people who confirmed it, are waiting, or were never sent it; trainings: per kind, how many people are trained, who is not, and what expires within 60 days. Every reply also carries cost_usd and balance_usd.

Inputs

Name	Type	What it is
`name`	string	Like ai-use-policy. Matches ^[a-z0-9][a-z0-9-]{0,79}$.
`training_kind`	string	One of: ai_literacy,privacy,security,safety,other.

The call

Over MCP, call hr_policy_status on https://api.conecto.chat/mcp/hr. Over REST:

Terminal

curl -X POST https://api.conecto.chat/v1/tools/hr_policy_status \
  -H "Authorization: Bearer $CONECTO_KEY" \
  -H "Content-Type: application/json" \
  -d '{"training_kind":"ai_literacy"}'

When it refuses

A refused call costs nothing and says what to do next.

Code	When	What to do
`not_found`404	No policy has that name.	Leave name out to see every policy.

More HR tools

All 23 tools

Give this to your agent.

Set up Conecto from https://conecto.chat/SKILL.md

See who confirmed policies and trainings

An example

Use it when

What it does

What comes back

Inputs

The call

When it refuses

More HR tools

Give this to your agent.