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review-cycle

Unified multi-dimensional code review with automated fix orchestration. Supports session-based (git changes) and module-based (path patterns) review modes with 7-dimension parallel analysis, iterative deep-dive, and automated fix pipeline. Triggers on "workflow:review-cycle", "workflow:review-session-cycle", "workflow:review-module-cycle", "workflow:review-cycle-fix".

62

Quality

73%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Risky

Do not use without reviewing

Fix and improve this skill with Tessl

tessl review fix ./.codex/skills/review-cycle/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

62%

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

This is a comprehensive orchestration skill with excellent workflow clarity and actionability—every phase has concrete code, clear sequencing, and robust error handling. However, it severely suffers from verbosity: the architecture is described three times in different formats (ASCII diagram, execution flow, data flow), progress tracking patterns are exhaustively enumerated, and content that belongs in phase reference docs is duplicated inline. The skill would benefit enormously from aggressive trimming, pushing detail into the referenced phase documents.

Suggestions

Remove redundant representations: keep either the ASCII architecture diagram OR the execution flow OR the data flow section—not all three. A single execution flow with phase references is sufficient.

Move the Subagent API Reference, Progress Tracking Pattern, and Error Handling tables into separate reference documents (e.g., subagent-api.md, error-handling.md) and link to them, since these are reference material not needed on every invocation.

Extract the inline Phase 7.5 implementation code into its own phase document (phases/07.5-export-task-json.md) consistent with how all other phases are structured.

Consolidate the progress tracking section to a single example pattern rather than exhaustively listing every phase transition—Claude can extrapolate the pattern from one example.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~400+ lines with extensive ASCII diagrams, redundant data flow representations (architecture diagram, execution flow, and data flow all repeat similar information), and detailed progress tracking patterns that could be in separate phase docs. The same phase sequence is described at least 3 times in different formats.

1 / 3

Actionability

The skill provides fully executable code examples for spawn_agent, wait_agent, close_agent, mode detection logic, progress tracking calls, and Phase 7.5 task export. Commands are copy-paste ready with concrete flag examples and specific JSON schemas.

3 / 3

Workflow Clarity

The multi-phase workflow is exceptionally well-sequenced with explicit conditional branching (Phase 3→4 vs 3→5), validation checkpoints (100% test pass rate in Phase 8, rollback on failure), error handling tables with blocking/non-blocking classification, and feedback loops (Phase 4 loops back to Phase 3 aggregation). Timeout escalation pattern for subagents is thorough.

3 / 3

Progressive Disclosure

The skill correctly references 9 phase documents for on-demand loading and includes a clear phase reference table. However, without bundle files provided, we cannot verify these references exist. More critically, Phase 7.5 is inlined with substantial code that could be in its own phase doc, and the SKILL.md itself contains too much detail that should be delegated to phase docs (e.g., full subagent API reference, complete progress tracking patterns, full error handling tables).

2 / 3

Total

9

/

12

Passed

Description

85%

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 technically detailed and comprehensive in explaining what the skill does and when it should be triggered. Its main weakness is that the trigger terms are system-level workflow commands rather than natural language phrases a user would actually say, which could hurt discoverability in natural conversation. The specificity and distinctiveness are strong, but the description reads more like internal documentation than a user-facing skill selector.

Suggestions

Add natural language trigger terms alongside the workflow commands, e.g., 'Use when the user asks to review code, check git changes, analyze a module, or fix code issues'

Include common user phrasings like 'code review', 'review my PR', 'check my changes', 'fix issues in my code' to improve natural language matching

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: session-based and module-based review modes, 7-dimension parallel analysis, iterative deep-dive, automated fix pipeline, and fix orchestration. These are concrete, specific capabilities.

3 / 3

Completeness

Clearly answers both 'what' (multi-dimensional code review with automated fix orchestration, session-based and module-based modes, 7-dimension analysis, fix pipeline) and 'when' (explicit triggers listed). The 'when' is addressed via the 'Triggers on' clause with specific trigger terms.

3 / 3

Trigger Term Quality

The trigger terms are explicit workflow commands ('workflow:review-cycle', etc.) rather than natural language terms a user would say. A user asking for a code review would say 'review my code', 'check my changes', or 'review this module' — not these prefixed workflow identifiers. Some relevant keywords like 'code review', 'git changes', and 'fix' are present in the body text.

2 / 3

Distinctiveness Conflict Risk

Highly distinctive with its specific workflow trigger commands, multi-dimensional analysis approach, and dual review modes (session-based vs module-based). The combination of these features and the explicit trigger prefixes make it very unlikely to conflict with other skills.

3 / 3

Total

11

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (509 lines); consider splitting into references/ and linking

Warning

Total

10

/

11

Passed

Repository
catlog22/Claude-Code-Workflow
Reviewed

Table of Contents

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