Agent skill

Mentorship Program

by sickn33 in sickn33/agentic-awesome-skills

Mentorship register: mentor and mentee pair, department, focus area, mentee goal, session counts, last and next session, overall rating, progress notes and status.

MITAuto-check passed

Install Mentorship Program

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

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

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills mentorship-program --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/mentorship-program .claude/skills/mentorship-program && 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
mentorship-program
GitHub stars
47k
Used in
1 other repo
Token cost
~3.7k tokens
SKILL.md length
1,397 words
Files
1
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

Mentorship register: mentor and mentee pair, department, focus area, mentee goal, session counts, last and next session, overall rating, progress notes and status.

  • Works in 5 steps: Identify intent → Ask only what is missing → Hold the internal context → …
  • Mentorship tracking
  • 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

Mentorship Program is an agent skill from sickn33/agentic-awesome-skills. Mentorship register: mentor and mentee pair, department, focus area, mentee goal, session counts, last and next session, overall rating, progress notes and status. Use for mentorship tracking.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

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

  • Mentorship tracking

Example prompts

  • “/mentorship-program”

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

Mentorship Program loads about 3.7k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 1,397 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

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). 1,397 words, ~3,661 tokens.

Download SKILL.mdSave it as .claude/skills/mentorship-program/SKILL.md (or your agent's skills folder).
name
mentorship-program
description
Mentorship register: mentor and mentee pair, department, focus area, mentee goal, session counts, last and next session, overall rating, progress notes and status. Use for mentorship tracking.
category
business
risk
safe
source
self
source_type
self
date_added
2026-09-26
author
WHOISABHISHEKADHIKARI
tags
sme, business, operations, database, csv, notion, sql, develop
source_repo
WHOISABHISHEKADHIKARI/sme-ops-system-builder

Mentorship Program

What it is: Internal mentoring.

Overview

Works out the smallest useful Mentorship Program 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: Scale stage. Table code: n/a.

When to Use This Skill

  • mentorship program
  • mentor matching
  • internal mentoring tracker
  • mentor mentee pairs

Also use it when the user says "internal mentoring", 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 many people want to be mentored?

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.

  • People - Mentees and mentors? / How many pairs? / Same team or cross-team?
  • Programme - How long? / Session cadence? / Structured or informal?
  • Matching - How matched today? / By skill or interest? / Who approves?
  • Current process - Anything running now? / How tracked? / What failed before?
  • Outcome - What do you need? / Matching, session tracking or feedback?

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: mentorship-program
intent: null            # setup | advice | review | fix | build | convert | export
scale: null             # Starter | Growth | Scale, only if the answer changes it
areas:
  "People": null
  "Programme": null
  "Matching": 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: Match on a stated goal rather than availability, and track only sessions and a closing rating.

Why this one: Mentorship fails when pairs are assigned by convenience and never meet. A stated goal for the mentee is what makes a pair worth recording.

Workflow: Mentee goal → Match → Sessions → Mid review → Close with rating

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
Mentorship Pair,Department,End Date,Focus Area,Last Session,Mentee Goal,Mentee Name,Mentor Name,Mentorship ID,Next Session,Overall Rating,Progress Notes,Sessions Completed,Sessions Planned,Start Date,Status
Priya Nair + Rohit Verma,Delivery,2026-11-27,Stakeholder management and commercial conversations.,2026-01-08,Lead two client calls end to end this quarter.,Priya Nair,Rohit Verma,,2026-01-22,4,Two of four goals on track. Delegation still needs work.,5,12,2026-02-02,Active
sql
CREATE TABLE mentorship_program (
  mentorship_pair VARCHAR(255),
  department VARCHAR(255),
  end_date DATE NOT NULL,
  focus_area VARCHAR(255),
  last_session DATE NOT NULL,
  mentee_goal VARCHAR(255),
  mentee_name VARCHAR(255),  -- relation -> target record
  mentor_name VARCHAR(255),  -- relation -> target record
  mentorship_id SERIAL PRIMARY KEY,
  next_session DATE NOT NULL,
  overall_rating VARCHAR(255),
  progress_notes TEXT,
  sessions_completed NUMERIC NOT NULL,
  sessions_planned NUMERIC NOT NULL,
  start_date DATE NOT NULL,
  status VARCHAR(100) NOT NULL,
  created_at TIMESTAMP DEFAULT NOW(),
  updated_at TIMESTAMP DEFAULT NOW()
);

CREATE INDEX idx_mentorship_program_status ON mentorship_program (status);
json
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "title": "Mentorship Program",
  "type": "object",
  "additionalProperties": false,
  "properties": {
      "Mentorship Pair": { "type": "string" },
      "Department": { "type": "string" },
      "End Date": { "type": "string", "format": "date" },
      "Focus Area": { "type": "string" },
      "Last Session": { "type": "string", "format": "date" },
      "Mentee Goal": { "type": "string" },
      "Mentee Name": { "type": "string" },
      "Mentor Name": { "type": "string" },
      "Mentorship ID": { "type": "integer" },
      "Next Session": { "type": "string", "format": "date" },
      "Overall Rating": { "type": "string" },
      "Progress Notes": { "type": "string" },
      "Sessions Completed": { "type": "number" },
      "Sessions Planned": { "type": "number" },
      "Start Date": { "type": "string", "format": "date" },
      "Status": { "type": "string" }
  },
  "required": [
      "End Date",
      "Last Session",
      "Next Session",
      "Sessions Completed",
      "Sessions Planned",
      "Start Date",
      "Status"
  ]
}
markdown
| CSV column | Notion property | Set after import |
|---|---|---|
| Mentorship Pair | Title | Use as the database title |
| Department | Text | Leave as Text |
| End Date | Date | Convert to Date |
| Focus Area | Text | Leave as Text |
| Last Session | Date | Convert to Date |
| Mentee Goal | Text | Leave as Text |
| Mentee Name | Relation (link to the target database) | Convert to Relation, link to the target database |
| Mentor Name | Relation (link to the target database) | Convert to Relation, link to the target database |
| Mentorship ID | Text (preserve source ID) | Keep imported IDs as Text; optionally add a separate Unique ID property |
| Next Session | Date | Convert to Date |
| Overall Rating | Text | Leave as Text |
| Progress Notes | Text | Leave as Text |
| Sessions Completed | Number | Convert to Number |
| Sessions Planned | Number | Convert to Number |
| Start Date | Date | Convert to Date |
| Status | Select (add options after import) | Convert to Select, add options: "Proposed", "Active", "Paused", "Completed", "Ended" |

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
1Mentorship PairtextVARCHAR(255)stringTextPriya Nair + Rohit Verma
2DepartmenttextVARCHAR(255)stringTextDelivery
3End DatedateDATEstring, format: dateDate2026-11-27
4Focus AreatextVARCHAR(255)stringTextStakeholder management and commercial conversations.
5Last SessiondateDATEstring, format: dateDate2026-01-08
6Mentee GoaltextVARCHAR(255)stringTextLead two client calls end to end this quarter.
7Mentee NamerelationVARCHAR(255)stringRelation (link to the target database)Priya Nair
8Mentor NamerelationVARCHAR(255)stringRelation (link to the target database)Rohit Verma
9Mentorship IDidSERIAL PRIMARY KEYintegerText (preserve source ID)(blank)
10Next SessiondateDATEstring, format: dateDate2026-01-22
11Overall RatingtextVARCHAR(255)stringText4
12Progress Noteslong_textTEXTstringTextTwo of four goals on track. Delegation still needs work.
13Sessions CompletednumberNUMERICnumberNumber5
14Sessions PlannednumberNUMERICnumberNumber12
15Start DatedateDATEstring, format: dateDate2026-02-02
16StatusselectVARCHAR(100)stringSelect (add options after import)Active
Show full SKILL.md (487 more words)Show less

Select Options

Status

Proposed | Active | Paused | Completed | Ended

Relations

Link fields: Mentee Name, Mentor Name

Examples

Prompt

We want to run mentoring for people joining the delivery team.

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

Q: How many pairs? A: Six.

Q: How long? A: Six months.

Q: How matched now? A: Not at all.

Recommended next step - offered, not built:

Match on a stated goal rather than availability, and track only sessions and a closing rating.

Workflow: Mentee goal → Match → Sessions → Mid review → Close with rating

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 match people automatically or send session reminders.
  • 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.

Reusable Prompt

I want to set up internal mentoring 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/mentorship-program 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

Mentorship Program 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.

Mentorship Program compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Mentorship Program this skillsickn33/agentic-awesome-skills47k1 repos~3.7kAutomated safety check: PassMIT
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Pair Programmingstaruhub/ClaudeSkills727—~482Automated safety check: PassMIT
Iot Registerruvnet/ruflo74k—~263Automated safety check: PassMIT
Qe Pair Programmingproffesor-for-testing/agentic-qe4956 repos~6kAutomated safety check: PassMIT
Focus Stylesthedaviddias/Front-End-Checklist74k—~639Automated safety check: PassMIT

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Questions about Mentorship Program

What does Mentorship Program do?

Mentorship register: mentor and mentee pair, department, focus area, mentee goal, session counts, last and next session, overall rating, progress notes and status. Mentorship Program is an agent skill from sickn33/agentic-awesome-skills. Mentorship register: mentor and mentee pair, department, focus area, mentee goal, session counts, last and next session, overall rating, progress notes and status.

When should I use Mentorship Program?

Mentorship Program fits situations like: mentorship tracking.

How do I install Mentorship Program in Claude Code?

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

How do I install Mentorship Program in Codex?

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

Can I use Mentorship Program 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 mentorship-program -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mentorship-program, .gemini/skills/mentorship-program, .github/skills/mentorship-program and .opencode/skills/mentorship-program in your project.

What does Mentorship Program need to run?

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

Does Mentorship Program 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 Mentorship Program 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 Mentorship Program use?

Mentorship Program 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 Mentorship Program use?

About 3.7k tokens (SKILL.md is roughly 15k 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 Mentorship Program?

Skills that share tags, products or a category with Mentorship Program: Daily Focus Board (github/awesome-copilot, 40k stars), Pair Programming (staruhub/ClaudeSkills, 727 stars), Iot Register (ruvnet/ruflo, 74k stars) and Qe Pair Programming (proffesor-for-testing/agentic-qe, 495 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mentorship Program?

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.