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mcpa-certification

AI-native tutor and onboarding workflow for the MCPA (Model Context Protocol Associate) certification in AI Engineering from Scratch. Use when a learner wants to prepare for the MCPA, resume their certification path, learn the next lesson interactively, run and verify practical labs, take the diagnostic or a full mock, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.

Quality

91%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is an operationally precise, multi-mode workflow with executable commands, explicit validation checkpoints, and error-recovery loops throughout. Its only real costs are a slightly long single-file layout with no reference bundle for separable material, and a few restated rules that could be tightened.

DimensionReasoningScore

Conciseness

The body is dense and operational — it teaches no concepts Claude already knows, and the time-sensitive 2026-07-28 protocol revision is properly framed with 'Present older revisions only as what's changed' and explicit deprecation of Roots, Sampling, Logging, and Dynamic Client Registration. Minor over-explanation remains (website optionality and state-archiving rules are each restated), matching the level-4 'efficient; minor instances that could be trimmed' anchor rather than the fully lean level 5.

4 / 5

Actionability

Guidance is fully executable: exact commands ('python3 <lesson-path>/code/main.py', 'python3 -m unittest discover -s <lesson-path>/code/tests -v', 'python3 scripts/check_mcpa_wire.py <lesson-path>'), a concrete raw-GitHub URL pattern, specific file paths, and a copy-paste-ready markdown template for MCPA-CERTIFICATION.md. This matches the level-5 anchor of copy-paste-ready commands covering the common cases.

5 / 5

Workflow Clarity

A numbered mode-selection algorithm routes to four modes, each with an explicit sequence (Recall → Explain and challenge → Run the practical lab → Verify understanding), explicit validation checkpoints ('Do not mark practical work verified if the runtime or tests did not actually run'), and error-recovery feedback loops ('If the quiz is below 70 percent, add the missed domain and lesson to the review queue'; 'Theory complete, lab pending'). This is the level-5 anchor with validation steps and feedback loops, not level 4 which allows checkpoint gaps.

5 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent), so all ~325 lines live in SKILL.md. Section structure per mode is clear and easy to navigate, but material that could sit in one-level-deep reference files — the full learner-state template, capstone boundaries, onboarding script — is inlined, which fits the level-4 'good structure; most content appropriately placed; minor organization gaps' anchor rather than the well-split level 5.

4 / 5

Total

18

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is a strong example: it names the exact certification, lists the skill's concrete capabilities, and provides an explicit 'Use when' clause with natural trigger phrases. The only weakness is that a few synonymous phrasings a learner might naturally use (e.g., 'study for', 'practice exam', 'exam prep') are not covered.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete actions — 'prepare for the MCPA, resume their certification path, learn the next lesson interactively, run and verify practical labs, take the diagnostic or a full mock, or remediate weak exam domains' — giving comprehensive coverage of the skill's capabilities. It matches the 'lists multiple specific concrete actions; comprehensive coverage' anchor, not level 4, since no meaningful capability is left out.

5 / 5

Completeness

It states clearly what the skill is ('AI-native tutor and onboarding workflow for the MCPA... certification in AI Engineering from Scratch') and gives an explicit 'Use when...' clause with concrete trigger phrases. This matches the level-5 anchor answering both what and when explicitly; level 4 would require the 'when' to be less specific.

5 / 5

Trigger Term Quality

Natural trigger phrases are strong ('prepare for the MCPA', 'resume their certification path', 'take the diagnostic or a full mock') and host tools are named (Claude Code, Codex, ChatGPT, Cursor), but common learner phrasings such as 'study for the exam', 'practice exam', or 'exam prep' are absent. Good keyword coverage with a few natural terms missing, which is the level-4 anchor rather than the comprehensive synonym coverage of level 5.

4 / 5

Distinctiveness Conflict Risk

A single named certification with dedicated triggers (MCPA, diagnostic, full mock, remediation, certification path) creates a clear niche with minimal overlap risk against generic tutoring or study skills. This fits the level-5 'clear niche with distinct triggers' anchor.

5 / 5

Total

19

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 2 missing

Warning

Total

15

/

16

Passed

Repository

rohitg00/ai-engineering-from-scratch

Path

skills/mcpa-certification/SKILL.md

Reviewed

Table of Contents

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