recognition-rewards – skill Khác cho agent AI

Recognition & Rewards

What it is: Celebrating excellence.

Overview

Works out the smallest useful Recognition & Rewards setup for the business in front of it, then

builds it only when asked. The default output is a short recommendation, not a

spreadsheet. Artifacts - CSV, SQL DDL, JSON Schema, Notion mapping - are produced on

request, from one field list so they cannot drift apart.

Layer: Layer 5: Develop. Fits: Growth stage. Table code: n/a.

When to Use This Skill

• employee recognition
• kudos board
• reward tracker
• employee appreciation log

Also use it when the user says "celebrating excellence", or describes the same process happening in a

spreadsheet, a document or someone inboxes.

Do not use it for: payroll calculation, tax filing, or legal advice. This skill produces

empty templates only - it never holds or processes real employee or customer data.

How It Works

Follow the shared execution contract. The module-specific rules below define only domain fields, decisions, calculations, and safety constraints.

Step 1 - Identify intent

Read the request and pick the intent before asking anything.

• "set up" or "build" or "create" -> the user wants artifacts; go to Step 2.
• "our process is ..." or "it is in a sheet" -> the user wants to move an existing process; capture it, then Step 2.
• "is this right" or "review" or "audit" -> the user wants a check, not a build; answer from what they share.
• "how do I ..." -> advice question; answer directly and offer the build only if it helps.

Ask only if this is the highest-value missing fact; otherwise proceed without an opener:

> Q: How often do you recognise people?

Step 2 - Ask only what is missing

Skip anything the user already answered, in any earlier message. Ask the rest one at a

time, and stop as soon as the remaining answers would not change the output.

• Cadence - Spot or monthly? / Who gives it? / Anyone or managers?
• Reward - Points, gift or cash? / Budget? / Extra time off?
• Visibility - Public or private? / Whole company or team? / Named or anonymous?
• Current process - Anything now? / Where is it captured? / Does anyone see it?
• Outcome - What do you need? / A log, a wall or reporting?

Never invent an answer. If the user does not know, record it as unknown and carry on.

Step 3 - Hold the internal context

Hold the answers in this shape. It stays internal - it is not shown to the user unless

they ask, and it never carries a value the user did not give.

module: recognition-rewards
intent: null            # setup | advice | review | fix | build | convert | export
scale: null             # Starter | Growth | Scale, only if the answer changes it
areas:
  "Cadence": null
  "Reward": null
  "Visibility": null
  "Current process": null
  "Outcome": null
requested_outputs: []   # csv | sql | json | notion | xlsx - requested formats only
confirmed_facts: []     # only what the user actually said
open_questions: []      # the unanswered ones, in the order worth asking

Step 4 - Recommend the smallest workflow

If an artifact was requested, build it after resolving essential missing facts. Otherwise give a short recommendation and offer the relevant artifact.

Recommended approach: Capture recognition as it happens, with a category so you can see what is being valued over time.

Why this one: Recognition programmes fail when entry is effortful. One line at the time of the event is enough; monthly retrospectives are never filled in.

Workflow: Recognition given → Category → Wall or summary → Monthly review

Step 5 - Build only on request

Once the user asks for it, derive the fields from the confirmed context and emit the

requested artifacts. For machine-readable text, keep prose outside the data; for files,

provide a usable link. Report material validation failures or limitations separately.

**A selected Notion output is rendered by notion-manual-import, so route the

Notion step there.** When the user selects Notion, hand that step to

@notion-manual-import: it holds the CSV, the property

mapping, the import steps and the verification checklist, and it renders the Field

Reference below instead of defining a table of its own. Do not restate the mapping

here and do not improvise the import steps. Manual CSV and mapping outputs need no

connection. For requested workspace changes, follow the shared contract: verify actual

tool access and the target before writing. A user saying "connected" is not tool evidence.

Never ask for a Notion password or token.

For an Excel-compatible CSV, use UTF-8 with a byte order mark so Excel opens the

text correctly. A CSV is not an .xlsx workbook; create .xlsx only when the user

requests a workbook.

A CSV carries no types, so after it, name the columns

that need a number, date or currency format applied.

Recognition Title,Category,Date,Department,Given By,Message,Month,Notes,Points Awarded,Rec-Rwd ID,Recognised Employee,Reward Type,Visibility,Year
Won the Northwind pitch,Team,2026-01-15,Delivery,Karan Malhotra,Thank you for preparing the synthetic example pitch and supporting the team.,2026-03,February awards sent; two nominations were duplicates of the same contribution.,50,,Aarav Sharma,Spot Award,Company-wide,2026

CREATE TABLE recognition_rewards (
  recognition_title VARCHAR(255),
  category VARCHAR(100) NOT NULL,
  date DATE NOT NULL,
  department VARCHAR(255),
  given_by VARCHAR(255),
  message VARCHAR(255),
  month VARCHAR(255),
  notes TEXT,
  points_awarded NUMERIC,
  rec_rwd_id SERIAL PRIMARY KEY,
  recognised_employee VARCHAR(255),
  reward_type VARCHAR(100) NOT NULL,
  visibility VARCHAR(255),
  year VARCHAR(255),
  created_at TIMESTAMP DEFAULT NOW(),
  updated_at TIMESTAMP DEFAULT NOW()
);

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "title": "Recognition & Rewards",
  "type": "object",
  "additionalProperties": false,
  "properties": {
      "Recognition Title": { "type": "string" },
      "Category": { "type": "string" },
      "Date": { "type": "string", "format": "date" },
      "Department": { "type": "string" },
      "Given By": { "type": "string" },
      "Message": { "type": "string" },
      "Month": { "type": "string" },
      "Notes": { "type": "string" },
      "Points Awarded": { "type": ["number", "null"] },
      "Rec-Rwd ID": { "type": "integer" },
      "Recognised Employee": { "type": "string" },
      "Reward Type": { "type": "string" },
      "Visibility": { "type": "string" },
      "Year": { "type": "string" }
  },
  "required": [
      "Category",
      "Date",
      "Reward Type"
  ]
}

| CSV column | Notion property | Set after import |
|---|---|---|
| Recognition Title | Title | Use as the database title |
| Category | Select (add options after import) | Convert to Select, add options: "Team", "Individual", "Department", "Company", "Values" |
| Date | Date | Convert to Date |
| Department | Text | Leave as Text |
| Given By | Text | Leave as Text |
| Message | Text | Leave as Text |
| Month | Text | Leave as Text |
| Notes | Text | Leave as Text |
| Points Awarded | Number | Convert to Number |
| Rec-Rwd ID | Text (preserve source ID) | Keep imported IDs as Text; optionally add a separate Unique ID property |
| Recognised Employee | Text | Leave as Text |
| Reward Type | Select (add options after import) | Convert to Select, add options: "Spot Award", "Gift", "Voucher", "Cash", "Time Off", "Recognition" |
| Visibility | Text | Leave as Text |
| Year | Text | Leave as Text |

The rows above are documentation examples only. Emit empty templates unless the user explicitly requests examples. Money stays currency, dates stay date,

and anything pointing at another table stays relation.

Field Reference

| # | Field | Type | SQL | JSON Schema | Notion | CSV example |

|---:|---|---|---|---|---|---|

| 1 | Recognition Title | text | VARCHAR(255) | string | Text | Won the Northwind pitch |

| 2 | Category | select | VARCHAR(100) | string | Select (add options after import) | Team |

| 3 | Date | date | DATE | string, format: date | Date | 2026-01-15 |

| 4 | Department | text | VARCHAR(255) | string | Text | Delivery |

| 5 | Given By | text | VARCHAR(255) | string | Text | Karan Malhotra |

| 6 | Message | text | VARCHAR(255) | string | Text | Thank you for preparing the synthetic example pitch and supporting the team. |

| 7 | Month | text | VARCHAR(255) | string | Text | 2026-03 |

| 8 | Notes | long_text | TEXT | string | Text | February awards sent; two nominations were duplicates of the same contribution. |

| 9 | Points Awarded | number | NUMERIC | number | Number | 50 |

| 10 | Rec-Rwd ID | id | SERIAL PRIMARY KEY | integer | Text (preserve source ID) | (blank) |

| 11 | Recognised Employee | text | VARCHAR(255) | string | Text | Aarav Sharma |

|

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