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receiving-code-review

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

75

1.34x
Quality

62%

Does it follow best practices?

Impact

97%

1.34x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/receiving-code-review/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

This is a strong, well-structured skill that provides genuinely useful behavioral guidance for code review reception — a task where Claude's default tendencies (performative agreement, blind implementation) need explicit correction. The actionability is excellent with concrete examples and decision trees. The main weakness is repetition across sections, where the same anti-patterns (performative agreement, no thanks) are illustrated multiple times in slightly different contexts, inflating token cost without proportional value.

Suggestions

Consolidate the repeated 'no performative agreement' examples — the Forbidden Responses, Acknowledging Correct Feedback, and Real Examples sections all illustrate the same anti-pattern. A single comprehensive examples section would save ~20 lines.

DimensionReasoningScore

Conciseness

The skill is mostly efficient and covers genuinely useful non-obvious guidance (verification before implementation, YAGNI checks, pushback patterns). However, there's notable repetition — the 'forbidden responses' examples appear in multiple sections (Forbidden Responses, Acknowledging Correct Feedback, Real Examples), and some rules are restated 3+ times. The 'no thanks' section over-explains a simple rule. Could be tightened by ~30%.

2 / 3

Actionability

Highly actionable with concrete examples throughout: specific do/don't response patterns, grep commands for YAGNI checks, exact GitHub API paths for thread replies, clear decision trees with IF/THEN logic, and real-world scenarios showing both wrong and right approaches. The guidance is specific enough to be directly followed.

3 / 3

Workflow Clarity

Clear multi-step sequences with explicit validation checkpoints: the main response pattern (READ→UNDERSTAND→VERIFY→EVALUATE→RESPOND→IMPLEMENT), the unclear feedback handling (STOP before implementing), the external reviewer checklist (5 verification steps), and the implementation order (clarify→blocking→simple→complex→test→verify regressions). Feedback loops are present for error recovery (push back → corrected → acknowledge factually).

3 / 3

Progressive Disclosure

For a standalone skill with no bundle files, the content is well-organized with clear section headers, logical progression from overview to specific scenarios, and appropriate use of tables and code blocks. The skill is self-contained and doesn't need external references. Sections are well-signaled and easy to navigate.

3 / 3

Total

11

/

12

Passed

Description

40%

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 effectively communicates when to use the skill (receiving code review feedback that may be unclear or questionable) but completely fails to describe what the skill actually does in concrete terms. It reads more like a philosophical stance or guiding principle than a skill description, leaving Claude unable to understand the specific actions or outputs this skill provides.

Suggestions

Add concrete actions the skill performs, e.g., 'Analyzes code review feedback for technical accuracy, verifies suggested changes against codebase context, and formulates evidence-based responses to reviewer comments.'

Expand trigger terms to include common variations like 'PR comments', 'pull request feedback', 'reviewer suggestions', 'code review response', and 'review comments'.

Replace the philosophical framing ('not performative agreement or blind implementation') with specific outputs or behaviors, e.g., 'generates counterarguments with code evidence when feedback is incorrect, or produces implementation plans when feedback is valid'.

DimensionReasoningScore

Specificity

The description does not list any concrete actions or capabilities. It describes a mindset ('technical rigor and verification') and anti-patterns ('not performative agreement or blind implementation') but never states what the skill actually does — no verbs like 'analyze', 'verify', 'compare', or 'respond'.

1 / 3

Completeness

The 'when' is explicitly addressed ('Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable'). However, the 'what does this do' is essentially absent — it describes a philosophy rather than concrete actions the skill performs.

2 / 3

Trigger Term Quality

It includes some relevant trigger terms like 'code review feedback' and 'implementing suggestions' that users might naturally mention. However, it misses common variations like 'PR comments', 'review comments', 'pull request feedback', 'reviewer suggestions', or 'code review response'.

2 / 3

Distinctiveness Conflict Risk

The focus on code review feedback response gives it a somewhat specific niche, but the lack of concrete actions means it could overlap with general code review skills, code analysis skills, or communication/response skills. The philosophical framing ('technical rigor', 'not performative agreement') doesn't help distinguish it functionally.

2 / 3

Total

7

/

12

Passed

Validation

100%

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

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
obra/superpowers
Reviewed

Table of Contents

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