Define a defensible micro-credential with explicit competencies, performance evidence, rubric levels, verification, metadata, renewal, and quality-assurance requirements.
This prompt has variables that can be replaced with your own information. Copy and use it with your preferred LLM, or try it out in the LearnerBox Prompt Playground.
Act as an experienced competency-based education and micro-credential design specialist.
Develop a digital badge competency rubric using the information below.
Credential purpose and audience:
{{credential_context}}
Competency or skill domain:
{{competency_domain}}
Industry, academic, or professional standards:
{{standards}}
Assessment evidence:
{{assessment_evidence}}
Credential level and scope:
{{credential_level}}
Quality and platform requirements:
{{quality_requirements}}
Design requirements:
1. Define the credential’s purpose, audience, scope, and value proposition.
2. Distinguish:
- participation;
- completion;
- knowledge;
- applied skill;
- demonstrated competency; and
- advanced performance.
3. Write clear competency statements using observable performance.
4. Break each competency into:
- knowledge;
- skill;
- judgment;
- application;
- evidence; and
- conditions.
5. Define required evidence that is authentic, verifiable, and sufficient.
6. Create a multi-level rubric with observable descriptors.
7. Identify minimum passing requirements and whether all competencies are mandatory.
8. Include assessor guidance, moderation, and evidence-verification procedures.
9. Define metadata such as:
- title;
- issuer;
- description;
- criteria;
- evidence;
- standards alignment;
- issue date;
- expiry or renewal;
- identity verification; and
- revocation conditions.
10. Include accessibility and alternative evidence routes that preserve the competency.
11. Define stacking or pathway relationships with other credentials.
12. Identify renewal, recertification, or currency requirements where appropriate.
13. Include quality-assurance, appeal, and audit procedures.
14. Do not invent accreditation, industry endorsement, platform features, legal status, or equivalence.
15. Flag decisions requiring employer, regulator, accreditor, assessment, or platform review.
Present the result as:
{{output_format}}
Include:
- credential purpose;
- competency framework;
- evidence requirements;
- multi-level rubric;
- passing rules;
- assessor guide;
- moderation and verification;
- badge metadata;
- accessibility provisions;
- stacking and pathways;
- renewal rules;
- quality assurance; and
- approval questions.Replace each variable shown in double curly brackets with accurate information from your own professional context.
{{credential_context}}
Example: Describe intended earners, use case, issuer, and value proposition.
Define why the credential exists and for whom.
{{competency_domain}}
Example: Describe the specific capability to be recognized.
Keep the credential narrow enough for defensible assessment.
{{standards}}
Example: Paste relevant approved competency or occupational standards.
Use current authoritative standards where applicable.
{{assessment_evidence}}
Example: Describe tasks, portfolios, observations, simulations, tests, or workplace evidence.
Evidence should directly demonstrate the competency.
{{credential_level}}
Example: Describe beginner, intermediate, advanced, credit-bearing, non-credit, stackable, or renewal expectations.
Clarify the credential’s depth and boundaries.
{{quality_requirements}}
Example: Provide issuer policy, verification, privacy, accessibility, metadata, appeals, and platform constraints.
Use actual platform and institutional requirements.
{{output_format}}
Choose the format needed for development or approval.
A defensible micro-credential design containing explicit competencies, authentic evidence, performance levels, passing rules, assessor guidance, metadata, accessibility, pathways, renewal, quality assurance, and approval requirements.
These characteristics describe the type of thinking, customization, and output structure involved in using this prompt effectively.
This breakdown explains how the prompt’s major components work together to guide the AI toward a useful, reliable, and well-structured response.
Positions the AI as a competency-based micro-credential specialist.
Defines purpose, competency, standards, evidence, level, and quality requirements.
Requires a complete competency rubric, evidence, verification, metadata, and quality framework.
Prevents invented endorsement, accreditation, platform capability, and equivalence.
Requires competency, evidence, rubric, passing, assessment, metadata, access, pathways, renewal, and QA.
Credential context, domain, standards, evidence, level, quality requirements, and output format.
AI-generated responses can contain errors, omissions, unsupported assumptions, outdated information, or recommendations that do not reflect your jurisdiction or professional context.
Verify calculations, evidence, regulations, standards, policies, and professional recommendations before relying on the result. The qualified professional remains responsible for the final decision.
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