Agent skill

Attendance

by sickn33 in sickn33/agentic-awesome-skills

Daily attendance register: check-in and check-out, hours worked, work mode, late minutes, leave and regularisation flags, as CSV, SQL, JSON Schema or Notion on request.

MITAuto-check passedDocuments & Office

Install Attendance

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill attendance -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills attendance --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/attendance .claude/skills/attendance && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
attendance
GitHub stars
47k
Used in
1 other repo
Token cost
~3.5k tokens
SKILL.md length
1,395 words
Files
1
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

Daily attendance register: check-in and check-out, hours worked, work mode, late minutes, leave and regularisation flags, as CSV, SQL, JSON Schema or Notion on request.

  • Works in 5 steps: Identify intent → Ask only what is missing → Hold the internal context → …
  • Tasks that involve CSV and tabular files
  • SKILL.md covers Overview, When to Use This Skill, How It Works and Field Reference, plus 9 more sections
  • Reaches json-schema.org

What it does

Attendance is an agent skill from sickn33/agentic-awesome-skills. Daily attendance register: check-in and check-out, hours worked, work mode, late minutes, leave and regularisation flags, as CSV, SQL, JSON Schema or Notion on request. Use for payroll input.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Documents & Office, covering CSV and tabular files and SQL. It works with SQL and Notion. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve CSV and tabular files
  • Tasks that involve SQL

Example prompts

  • “/attendance”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Identify intent
  2. Ask only what is missing
  3. Hold the internal context
  4. Recommend the smallest workflow
  5. Build only on request

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml, csv, sql, json and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • json-schema.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Attendance loads about 3.5k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 1,395 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT licence (© sickn33). 1,395 words, ~3,528 tokens.

Download SKILL.mdSave it as .claude/skills/attendance/SKILL.md (or your agent's skills folder).
name
attendance
description
Daily attendance register: check-in and check-out, hours worked, work mode, late minutes, leave and regularisation flags, as CSV, SQL, JSON Schema or Notion on request. Use for payroll input.
category
business
risk
safe
source
self
source_type
self
date_added
2026-09-26
author
WHOISABHISHEKADHIKARI
tags
sme, business, operations, database, csv, notion, sql, manage
source_repo
WHOISABHISHEKADHIKARI/sme-ops-system-builder

Attendance

What it is: Daily check-in, check-out, late and absent records.

Overview

Works out the smallest useful Attendance 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 4: Manage. Fits: Starter stage. Table code: n/a.

When to Use This Skill

  • attendance tracker
  • daily attendance sheet
  • check in check out log
  • absent and late tracker

Also use it when the user says "daily check-in, check-out, late and absent records", 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: What are your working hours?

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.

  • Hours - Shift timings? / Flexible or fixed? / Any night shift?
  • Method - Check in, check out or both? / How recorded? / Self or auto?
  • Rules - Late tolerance? / Half day rules? / Geofence needed?
  • Current process - How is it done now? / Biometric, app or paper? / What gets disputed?
  • Outcome - What do you need? / A record, payroll input or reports?

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.

yaml
module: attendance
intent: null            # setup | advice | review | fix | build | convert | export
scale: null             # Starter | Growth | Scale, only if the answer changes it
areas:
  "Hours": null
  "Method": null
  "Rules": 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: Collect one row per person per day, and only build rules for the cases that actually happen. Overtime and payroll join later if needed.

Why this one: Attendance fails when corrections have no owner. Add a regularisation step and the record stays trustworthy without surveillance.

Workflow: Daily log → Late or absent flag → Correction request → Manager approval → Monthly report

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.

csv
Attendance Record,Employee Name,Department,Date,Check-in Time,Check-out Time,Hours Worked,Work Mode,Attendance Status,Late (Minutes),On Approved Leave,Manager,Regularisation Requested,Notes,Attendance ID
ATT-EXAMPLE-001,Example Employee,Delivery,2026-01-15,09:58,18:30,8.5,Office,Present,12,FALSE,Example Manager,FALSE,"Late arrivals cluster on Mondays; discussed with the team rather than logged as a penalty.",
sql
CREATE TABLE attendance (
  attendance_record VARCHAR(255),
  employee_name VARCHAR(255),
  department VARCHAR(255),
  date DATE NOT NULL,
  check_in_time VARCHAR(255),
  check_out_time VARCHAR(255),
  hours_worked NUMERIC NOT NULL,
  work_mode VARCHAR(255),
  attendance_status VARCHAR(100) NOT NULL,
  late_minutes NUMERIC NOT NULL,
  on_approved_leave BOOLEAN NOT NULL,
  manager VARCHAR(255),
  regularisation_requested BOOLEAN NOT NULL,
  notes TEXT,
  attendance_id SERIAL PRIMARY KEY,
  created_at TIMESTAMP DEFAULT NOW(),
  updated_at TIMESTAMP DEFAULT NOW()
);
json
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "title": "Attendance",
  "type": "object",
  "additionalProperties": false,
  "properties": {
      "Attendance Record": { "type": "string" },
      "Employee Name": { "type": "string" },
      "Department": { "type": "string" },
      "Date": { "type": "string", "format": "date" },
      "Check-in Time": { "type": "string" },
      "Check-out Time": { "type": "string" },
      "Hours Worked": { "type": "number" },
      "Work Mode": { "type": "string" },
      "Attendance Status": { "type": "string" },
      "Late (Minutes)": { "type": "number" },
      "On Approved Leave": { "type": "boolean" },
      "Manager": { "type": "string" },
      "Regularisation Requested": { "type": "boolean" },
      "Notes": { "type": "string" },
      "Attendance ID": { "type": "integer" }
  },
  "required": [
      "Date",
      "Hours Worked",
      "Attendance Status",
      "Late (Minutes)"
  ]
}
markdown
| CSV column | Notion property | Set after import |
|---|---|---|
| Attendance Record | Title | Use as the database title |
| Employee Name | Text | Leave as Text |
| Department | Text | Leave as Text |
| Date | Date | Convert to Date |
| Check-in Time | Text | Leave as Text |
| Check-out Time | Text | Leave as Text |
| Hours Worked | Number | Convert to Number |
| Work Mode | Text | Leave as Text |
| Attendance Status | Select (add options after import) | Convert to Select, add options: "Present", "Late", "Absent", "On Leave", "Half Day", "Holiday" |
| Late (Minutes) | Number | Convert to Number |
| On Approved Leave | Checkbox | Convert to Checkbox |
| Manager | Text | Leave as Text |
| Regularisation Requested | Checkbox | Convert to Checkbox |
| Notes | Text | Leave as Text |
| Attendance ID | Text (preserve source ID) | Keep imported IDs as Text; optionally add a separate Unique ID property |

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

#FieldTypeSQLJSON SchemaNotionCSV example
1Attendance RecordtextVARCHAR(255)stringTextATT-EXAMPLE-001
2Employee NametextVARCHAR(255)stringTextExample Employee
3DepartmenttextVARCHAR(255)stringTextDelivery
4DatedateDATEstring, format: dateDate2026-01-15
5Check-in TimetextVARCHAR(255)stringText09:58
6Check-out TimetextVARCHAR(255)stringText18:30
7Hours WorkednumberNUMERICnumberNumber8.5
8Work ModetextVARCHAR(255)stringTextOffice
9Attendance StatusselectVARCHAR(100)stringSelect (add options after import)Present
10Late (Minutes)numberNUMERICnumberNumber12
11On Approved LeavecheckboxBOOLEANbooleanCheckboxFALSE
12ManagertextVARCHAR(255)stringTextExample Manager
13Regularisation RequestedcheckboxBOOLEANbooleanCheckboxFALSE
14Noteslong_textTEXTstringTextLate arrivals cluster on Mondays; discussed with the team rather than logged as a penalty.
15Attendance IDidSERIAL PRIMARY KEYintegerText (preserve source ID)(blank)
Show full SKILL.md (500 more words)Show less

Select Options

Attendance Status

Present | Late | Absent | On Leave | Half Day | Holiday

Relations

Link fields: none

Examples

Prompt

We need attendance for payroll and half-days are a mess.

Context first - one question per message, nothing already answered:

Q: Shift timings? A: 9 to 6.

Q: How recorded? A: Manual, in a register.

Q: What gets disputed? A: Half days mostly.

Recommended next step - offered, not built:

Collect one row per person per day, and only build rules for the cases that actually happen. Overtime and payroll join later if needed.

Workflow: Daily log → Late or absent flag → Correction request → Manager approval → Monthly report

Want the CSV, SQL, JSON Schema and Notion mapping for this?

Best Practices

  • Build when requested; recommend and offer a build for advice-only requests.
  • One question per message. A batched intake reads as a form and gets guessed at.
  • Keep display names identical across CSV and JSON; document normalized SQL identifiers.
  • Use relation for anything that points at another table, text only for free text.
  • Money fields are currency, never text. Dates are date, never free text.
  • If the user requests an example row, keep it obviously fake so nobody imports it as real data.

Limitations

  • Empty template only. It does not compute payroll, tax, leave balances or KPIs.
  • Notion relations need both databases imported before the link column resolves.
  • Select options are a starting set. Rename them to match how the business talks.
  • No automation, reminders or sync. Those need the integration layer.
  • Does not enforce punctuality, geofence location or decide payroll.
  • Legal, tax and HR review is still required before this drives real decisions.

Security & Safety Notes

  • Never fill in real names, salaries, medical or banking data. Placeholders only.
  • Label example rows as synthetic, and keep bank details masked.
  • Local reads, generation commands, and validation are part of a requested artifact build. External writes, messages, provisioning, and publication require authorization for that action and target; existing explicit authorization does not need to be repeated.
  • If sensitive data is supplied, avoid repeating unnecessary identifiers. Use only what the requested review needs; keep generated templates empty. Do not claim deletion from the conversation or service storage.
  • Privacy, legal and disciplinary cases need a qualified human reviewer before anything is acted on.

Common Pitfalls

  • Problem: a static mapping is described as a completed workspace build. Solution: deliver manual mappings without a connection; claim a live change only after the authorized tool operation succeeds.
  • Problem: asked all six questions in one message. Solution: ask one, wait, and drop any the first answer already covered.
  • Problem: built a full system when one table was asked for. Solution: build what was requested; mention the parent skill separately.
  • Problem: all four artifacts drift apart. Solution: derive all four from the field list in this file, never by hand.
  • Problem: Notion import shows every column as Text. Solution: that is expected. Apply the property mapping table once, after import.
  • Module Catalog - find the relevant module, then read its skill.
  • @people-directory - the employee master record most modules link to.
  • @notification-reminder-hub - turns due dates in this module into reminders.

Reusable Prompt

I want to set up daily check-in, check-out, late and absent records for my company.
Ask me one short question at a time, and only about what I have not already told you.
Then recommend the smallest setup that fits, and wait for me to ask before you build it.
When I ask, output CSV, SQL DDL, JSON Schema, a Notion property mapping or an Excel workbook. Data only.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/attendance of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 680176d

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Attendance next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Attendance compared with similar skills
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Attendance this skillsickn33/agentic-awesome-skills47k1 repos~3.5kAutomated safety check: PassMIT
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Exportai-analyst-lab/ai-analyst304—~3.8kAutomated safety check: PassMIT
Data Processingjeremylongshore/tons-of-skills-marketplace2.8k—~1.3kAutomated safety check: PassMIT
Rust SQL Testshencangsheng/easydb_app590—~1.2kAutomated safety check: PassMIT
Mendix Odata Pushdownmendixlabs/mxcli129—~2.5kAutomated safety check: PassApache-2.0

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Works with

Questions about Attendance

What does Attendance do?

Daily attendance register: check-in and check-out, hours worked, work mode, late minutes, leave and regularisation flags, as CSV, SQL, JSON Schema or Notion on request. Attendance is an agent skill from sickn33/agentic-awesome-skills. Daily attendance register: check-in and check-out, hours worked, work mode, late minutes, leave and regularisation flags, as CSV, SQL, JSON Schema or Notion on request.

When should I use Attendance?

Attendance fits situations like: tasks that involve CSV and tabular files; tasks that involve SQL.

How do I install Attendance in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill attendance -a claude-code`. Or copy the skill folder (skills/attendance in sickn33/agentic-awesome-skills) into .claude/skills/attendance in your project. Claude Code loads it when a task matches its description.

How do I install Attendance in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill attendance -a codex`. Or copy the skill folder (skills/attendance in sickn33/agentic-awesome-skills) into .agents/skills/attendance in your project. Codex loads it when a task matches its description.

Can I use Attendance in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill attendance -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/attendance, .gemini/skills/attendance, .github/skills/attendance and .opencode/skills/attendance in your project.

What does Attendance need to run?

SKILL.md names no scripts, command-line tools or credentials: Attendance is instructions for the agent only.

Does Attendance access the network?

SKILL.md names 1 domain. In commands or code: json-schema.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Attendance safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Attendance use?

Attendance is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Attendance use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Attendance?

Skills that share tags, products or a category with Attendance: Data Explore (amd/gaia, 1.6k stars), Export (ai-analyst-lab/ai-analyst, 304 stars), Data Processing (jeremylongshore/tons-of-skills-marketplace, 2.8k stars) and Rust SQL Test (shencangsheng/easydb_app, 590 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Attendance?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.