Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
Install with Tessl CLI
npx tessl i github:wshobson/agents --skill code-review-excellence71
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillAgent success when using this skill
Validation for skill structure
Review format and severity labeling
Template: Summary section
100%
100%
Template: Strengths section
100%
100%
Template: Required Changes section
100%
100%
Template: Suggestions section
100%
100%
Template: Verdict section
62%
100%
Blocking label used
60%
100%
Nit/suggestion labels used
50%
100%
Praise label used
50%
100%
Question approach
0%
0%
Collaborative language
20%
40%
Identifies SQL injection
100%
100%
Identifies weak hashing
100%
100%
Without context: $0.2463 · 1m 32s · 8 turns · 57 in / 4,429 out tokens
With context: $0.6363 · 2m 25s · 26 turns · 25 in / 6,517 out tokens
TypeScript-specific bug detection
Flags 'any' in Props
100%
100%
Flags 'any' in api-client
100%
100%
Flags unhandled async errors
100%
100%
Clear verdict
75%
100%
Flags prop mutation
100%
100%
Does NOT flag formatting/style
100%
100%
Question approach
0%
0%
Collaborative language
10%
80%
Flags test mutation issue
100%
100%
Includes positive feedback
100%
100%
Without context: $0.2452 · 1m 27s · 8 turns · 57 in / 4,344 out tokens
With context: $0.4360 · 2m 7s · 13 turns · 14 in / 6,289 out tokens
Python-specific bug detection
Flags mutable default: metadata
100%
100%
Flags mutable default: channels
100%
100%
Flags mutable default: preferences
100%
100%
Flags mutable class attributes
100%
100%
Flags broad exception catch
100%
100%
Flags implementation-testing in tests
80%
100%
Does NOT flag formatting/style
100%
100%
Question approach
0%
50%
Collaborative language
20%
70%
Includes positive feedback
0%
100%
Without context: $0.3414 · 1m 57s · 10 turns · 11 in / 5,962 out tokens
With context: $0.4924 · 2m 17s · 17 turns · 64 in / 6,948 out tokens
Table of Contents
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