Skip to main content

project-review

Use when evaluating a completed or in-progress project across scope, correctness, quality, testing, and learning outcomes using structured Praise-Critique-Grow feedback.

Jump to install

Source facts

Repository
yugash007/edu-agent-skills
Last source activity
May 18, 2026 at 16:48
Detected SKILL.md language
English
Stars
7
Forks
2

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

File Explorer
3 files

Showing SKILL.md

SKILL.md
Source instructions · Read-only preview
name
project-review
description
Use when evaluating a completed or in-progress project across scope, correctness, quality, testing, and learning outcomes using structured Praise-Critique-Grow feedback.
version
1.1.0
authors
["edu-agent-skills contributors"]
tags
["projects","review","feedback","assessment"]
status
stable
# Purpose Provide structured, constructive review of a learner's project at a milestone or completion checkpoint. Combines technical evaluation with learning-outcome assessment. Uses Praise-Critique-Grow to maintain learner motivation while surfacing real issues. # Activation - Milestone reached in `build-with-me`. Feature or project completed. Learner asks for feedback on their work. Pre-submission review (assignment, portfolio, interview take-home). - **Skip if**: project hasn't started. Learner needs concept help → `teach-concept`. Active debugging in progress → `debug-teacher`. - **Routing**: issues found → use `challenge-generator` for targeted practice. Concept gaps → `teach-concept`. Design issues → `architecture-review`. Log weak areas to `weak-area-tracker`. # Inputs - Project/feature code and documentation, original requirements/scope, learner's stated goals, relevant assessment criteria. # Review Dimensions - **Scope**: does it meet stated requirements? Scope creep? Missing features? - **Correctness**: does it produce correct results? Edge cases handled? - **Code Quality**: readability, naming, structure, DRY, separation of concerns. - **Testing**: test coverage, test quality, edge case testing. - **Learning Outcomes**: what did the learner demonstrate they understand? What gaps remain? # Workflow 1. **Self-Assessment** — Ask learner first: "What do you think went well? What would you change?" This surfaces their self-awareness before external feedback. 2. **Review** — Evaluate across all 5 dimensions. Note strengths and issues with specific code/design references. 3. **Praise** — Start with 2–3 specific strengths. Reference actual decisions/code, not generic compliments. 4. **Critique** — List issues priority-ordered. Each: dimension, description, severity, specific code reference. Max 5 issues per review — more overwhelms. 5. **Grow** — For each major issue: one concrete next action. Frame as growth opportunity, not failure. Include a learning recommendation (skill or concept to revisit). 6. **Retrospective** — Ask one synthesis question: "What's the most important thing you learned from building this?" Record answer for `learning-memory`. # Rules - DO: require self-assessment before giving feedback. - DO: praise specific decisions, not generic effort. - DO: limit critique to top 5 issues — prioritize by impact. - DO: frame growth actions as opportunities, not failures. - DO: end with a retrospective question and record the answer. - DON'T: start with criticism — always Praise first. - DON'T: give vague feedback ("good job" / "needs work"). - DON'T: rewrite the learner's code — point to issues and let them fix. - DON'T: skip the self-assessment — it builds metacognitive skill. # Output Responses should contain: self-assessment prompt, praise (2–3 specific strengths), critique (issues with dimension + severity + code reference), grow (next actions + learning recommendations), and retrospective question. Format naturally. # Checklist - [ ] Self-assessment requested before external feedback. - [ ] Praise references specific code/decisions. - [ ] Critique limited to top 5 issues, priority-ordered. - [ ] Retrospective question asked and answer recorded.
View on GitHub