techdebt

Technical debt detection and remediation. Run at session end to find duplicated code, dead imports, security issues, and complexity hotspots. Triggers: 'find tech debt', 'scan for issues', 'check code quality', 'wrap up session', 'ready to commit', 'before merge', 'code review prep'. Always uses parallel subagents for fast analysis.

Install with Tessl CLI

npx tessl i github:NeverSight/skills_feed --skill techdebt

What are skills?

Review — 85%

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Validation — 11 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

Evaluation results

84%

30%

Security Audit: Python Backend API

Security vulnerability classification and report format

Criteria

Without context

With context

Report header: Debt Score

100%

Report header: Scope

100%

Summary table present

100%

Critical Issues section

25%

100%

Hardcoded secret as P0

100%

SQL injection as P0

100%

Insecure crypto as P0

Python-specific: yaml.load

100%

eval/exec as P1

File:line format

100%

Impact field per finding

100%

Fix field per finding

100%

Recommendations section

100%

Without context: $0.2392 · 1m 21s · 8 turns · 11 in / 4,782 out tokens

With context: $0.9741 · 1m 39s · 9 turns · 13 in / 5,641 out tokens

95%

53%

Code Quality Report: Order Processing Module

Complexity/duplication thresholds and summary report structure

Criteria

Without context

With context

Summary table: 4 categories

50%

100%

Debt Score present

100%

Complexity P1 threshold

100%

Function length P1 threshold

100%

Duplication P1 classification

100%

Duplication P2 classification

87%

Dead code: unused imports

50%

100%

File:line location format

25%

100%

Findings grouped by file

25%

50%

Refactoring suggestion for complexity

75%

100%

High Priority (P1) section

100%

Recommendations section

100%

Without context: $0.2974 · 1m 45s · 8 turns · 13 in / 5,874 out tokens

With context: $1.5947 · 5m 21s · 28 turns · 4,577 in / 16,091 out tokens

82%

-16%

Pre-Commit Code Cleanup: Data Pipeline Service

Dead code safe removal criteria and auto-fix safety rules

Criteria

Without context

With context

Dead imports as safe-fix

100%

Security NOT auto-fixable

100%

50%

Complexity NOT auto-fixable

100%

Safe removal: no external refs

100%

Safe removal: not public API

80%

70%

Orphaned function detected

100%

Unreachable code detected

100%

Findings grouped by file

100%

File:line location format

100%

Impact field present

100%

Fix field present

100%

Recommendations section

100%

Without context: $0.5042 · 2m 49s · 18 turns · 25 in / 9,674 out tokens

With context: $1.4309 · 5m 7s · 29 turns · 713 in / 15,933 out tokens

Evaluated: about 13 hours ago
Agent: Claude Code

Table of Contents

Security Audit: Python Backend API Code Quality Report: Order Processing Module Pre-Commit Code Cleanup: Data Pipeline Service

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