Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/thapaliyabikendra/ai-artifactsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/thapaliyabikendra/ai-artifacts/tech-debt)<a href="https://agentmods.dev/commands/thapaliyabikendra/ai-artifacts/tech-debt"><img src="https://agentmods.dev/badge/commands/thapaliyabikendra/ai-artifacts/tech-debt.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.02372 |
| Opus 5 | $0.00000 | $0.01186 |
| Sonnet 5 | $0.00000 | $0.00474 |
| Haiku 4.5 | $0.00000 | $0.00237 |
Grade A, and why
tech-debt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
94% identical to tech-debt — 60 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Debt Analysis and Remediation
You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create actionable remediation plans.
Context
The user needs a comprehensive technical debt analysis to understand what's slowing down development, increasing bugs, and creating maintenance challenges. Focus on practical, measurable improvements with clear ROI.
Requirements
$ARGUMENTS
Instructions
1. Technical Debt Inventory
Conduct a thorough scan for all types of technical debt:
Code Debt
-
Duplicated Code
- Exact duplicates (copy-paste)
- Similar logic patterns
- Repeated business rules
- Quantify: Lines duplicated, locations
-
Complex Code
- High cyclomatic complexity (>10)
- Deeply nested conditionals (>3 levels)
- Long methods (>50 lines)
- God classes (>500 lines, >20 methods)
- Quantify: Complexity scores, hotspots
-
Poor Structure
- Circular dependencies
- Inappropriate intimacy between classes
- Feature envy (methods using other class data)
- Shotgun surgery patterns
- Quantify: Coupling metrics, change frequency
Architecture Debt
-
Design Flaws
- Missing abstractions
- Leaky abstractions
- Violated architectural boundaries
- Monolithic components
- Quantify: Component size, dependency violations
-
Technology Debt
- Outdated frameworks/libraries
- Deprecated API usage
- Legacy patterns (e.g., callbacks vs promises)
- Unsupported dependencies
- Quantify: Version lag, security vulnerabilities
Testing Debt
-
Coverage Gaps
- Untested code paths
- Missing edge cases
- No integration tests
- Lack of performance tests
- Quantify: Coverage %, critical paths untested
-
Test Quality
- Brittle tests (environment-dependent)
- Slow test suites
- Flaky tests
- No test documentation
- Quantify: Test runtime, failure rate
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 371 lines · 0 tokens per session scan A bd2a670f5423
tech-debt is a command published in the GitHub repository thapaliyabikendra/ai-artifacts (24 stars, last pushed 5mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 2,372 tokens. A static security scan graded it A with 0 findings. It is 94% identical to tech-debt, differing in 60 lines, and is treated as a copy.
Other commands, from other repositories
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
review-sdk-app
Review and validate a Claude Agent SDK application against best practices.
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.