competency-matrix – skill Khác cho agent AI

Competency Matrix

What it is: Skill levels.

Overview

Works out the smallest useful Competency Matrix 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

• competency matrix
• skills framework
• role competency model
• capability matrix

Also use it when the user says "skill levels" for roles (what each role must show), or

describes the same process happening in a spreadsheet, a document or someone's inbox.

Do not use it for: payroll calculation, tax filing, or legal advice; assessing named people

against expected levels (that is skill-gap-analysis); or certifying competence. 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" -> set up; go to Step 2.
• "our process is ..." or "it is in a sheet" -> import; capture it, then Step 2.
• "is this right" or "review" or "audit" -> review; answer from what they share. Do not open an intake question.
• "how do I ..." -> report; answer directly and offer the build only if it helps.
• "fix" -> fix; correct confirmed defects in the supplied material.

One message, one question, no batching. If intent is set up or import and the user has

not named the roles, open with:

> Q: Which roles need a competency model?

If they already named roles, ask the next missing fact that would change the recommendation

or the requested artifact. Never ask a question whose answer would not change the result.

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.

• Roles - Which roles? Skip if already named. This table also stores two different

"level" facts. Do not ask "How many levels?" until you know which: Grade Level

(job grade) or Expected Level (proficiency). First ask which they mean, using those

two names. After that answer, ask how many and what they are called.

• Competencies - Which competencies? / Derived from what?
• Assessment - Who assesses? / Self or manager? / How often?
• Current process - Is anything documented? / Training linked? / What is missing?
• Outcome - What do you need? A matrix, an assessment sheet, or a link to a gap record?

Do not assume a skill-gap table unless they asked for that link.

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

Country and software are not required inputs for a country-neutral, tool-neutral

competency-matrix review. Ask for either only when the user supplied country- or

tool-specific requirements that materially change the requested result.

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: competency-matrix
intent: null            # setup | advice | review | fix | build | convert | export
scale: null             # Starter | Growth | Scale, only if the answer changes it
areas:
  "Roles": null
  "Competencies": null
  "Assessment": 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 artifacts were requested, build from confirmed facts after resolving essential gaps. For advice-only requests, give a short recommendation and offer: "Want me to build the CSV, SQL DDL, JSON Schema, Notion mapping, or an

Excel workbook from these confirmed rules?"

Recommended approach: Define a small set of proficiency levels and attach each competency

to the confirmed roles. Include grades only when the user named them. Mention a gap or

training link only when the user confirmed they need one.

Why this one: A matrix that is not attached to roles (and, when confirmed, to a later

assessment or gap record) does not change any decision.

Workflow: Roles → Competencies → Level expectations → Assessment. Add a gap and training

link only when that outcome was confirmed.

Step 5 - Build only on request

Once the user asks for it, emit the artifacts as data only. No preamble, no summary, no

closing line. The Field Reference is the documented starting shape. If the user confirmed

different grade names, proficiency labels, or category names, emit those as the select

options instead of the starting set. Do not keep a five-level proficiency list when they

confirmed four. Do not invent competencies, roles, or grades they did not supply.

**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. This shape has no number, date, or currency columns to format after import.

Competency,Category,Job Title,Grade Level,Expected Level,Description,Assessment Method,Linked Skill Area,Competency ID
Example Competency,General,Example Role,L1,1 - Beginner,"States the expected stakeholder work at this grade.",Manager observation plus a practical task,SKL-EXAMPLE-001,

CREATE TABLE competency_matrix (
  competency VARCHAR(255),
  category VARCHAR(100) NOT NULL,
  job_title VARCHAR(255),
  grade_level VARCHAR(100),
  expected_level VARCHAR(100) NOT NULL,
  description TEXT,
  assessment_method VARCHAR(255),
  linked_skill_area VARCHAR(255),  -- text reference; not a foreign key in this build
  competency_id SERIAL PRIMARY KEY,
  created_at TIMESTAMP DEFAULT NOW(),
  updated_at TIMESTAMP DEFAULT NOW()
);

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "title": "Competency Matrix",
  "type": "object",
  "additionalProperties": false,
  "properties": {
      "Competency": { "type": "string" },
      "Category": { "type": "string" },
      "Job Title": { "type": "string" },
      "Grade Level": { "type": "string" },
      "Expected Level": { "type": "string" },
      "Description": { "type": "string" },
      "Assessment Method": { "type": "string" },
      "Linked Skill Area": { "type": "string" },
      "Competency ID": { "type": "integer" }
  },
  "required": [
      "Category",
      "Expected Level"
  ]
}

| CSV column | Notion property | Set after import |
|---|---|---|
| Competency | Title | Use as the database title |
| Category | Select (add options after import) | Convert to Select, add options: "General", "Operations", "Finance", "People", "Compliance" |
| Job Title | Text | Leave as Text |
| Grade Level | Select (add options after import) | Convert to Select, add options: "L1", "L2", "L3", "L4", "L5", "M1", "M2" |
| Expected Level | Select (add options after import) | Convert to Select, add options: "1 - Beginner", "2 - Basic", "3 - Proficient", "4 - Advanced", "5 - Expert" |
| Description | Text | Leave as Text |
| Assessment Method | Text | Leave as Text |
| Linked Skill Area | Text | Leave as Text, NOT a Relation. The skill-gap table is not part of this build, so no target database exists to link to |
| Competency 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. This module has no money, date, or relation fields.

Field Reference

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

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

| 1 | Competency | text | VARCHAR(255) | string | Text | Example Competency |

| 2 | Category

… (nội dung đầy đủ có trong gói tải về)