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.
npx skills add frabcd/codex-ai-game-studio --skill tech-debtgit clone --depth 1 https://github.com/frabcd/codex-ai-game-studioWrote 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/skills/frabcd/codex-ai-game-studio/tech-debt)<a href="https://agentmods.dev/skills/frabcd/codex-ai-game-studio/tech-debt"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/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 | $0.00033 | $0.01361 |
| Opus 5 | $0.00016 | $0.00681 |
| Sonnet 5 | $0.00007 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
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 3d 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
91% identical to tech-debt — 18 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Port provenance: adapted from the pinned upstream source at
984023ddac0d5e27624f2baacde6105e45de375funder MIT; see the repository parity ledger for the exact path and blob.
Phase 1: Parse Subcommand
Determine the mode from the argument:
scan— Scan the codebase for tech debt indicatorsadd— Add a new tech debt entry manuallyprioritize— Re-prioritize the existing debt registerreport— Generate a summary report of current debt status
If no subcommand is provided, output usage and stop. Verdict: FAIL — missing required subcommand.
Phase 2A: Scan Mode
Search the codebase for debt indicators:
TODOcomments (count and categorize)FIXMEcomments (these are bugs disguised as debt)HACKcomments (workarounds that need proper solutions)@deprecatedmarkers- Duplicated code blocks (similar patterns in multiple files)
- Files over 500 lines (potential god objects)
- Functions over 50 lines (potential complexity)
Categorize each finding:
- Architecture Debt: Wrong abstractions, missing patterns, coupling issues
- Code Quality Debt: Duplication, complexity, naming, missing types
- Test Debt: Missing tests, flaky tests, untested edge cases
- Documentation Debt: Missing docs, outdated docs, undocumented APIs
- Dependency Debt: Outdated packages, deprecated APIs, version conflicts
- Performance Debt: Known slow paths, unoptimized queries, memory issues
Present the findings to the user.
Ask: "May I write these findings to docs/tech-debt-register.md?"
If yes, update the register (append new entries, do not overwrite existing ones). Verdict: COMPLETE — scan findings written to register.
If no, stop here. Verdict: BLOCKED — user declined write.
Phase 2B: Add Mode
Ask the user for the description, affected files, and impact if left unfixed (plain text prompts).
Then use the available user-input mechanism to collect the category:
- Prompt: "What category does this tech debt belong to?"
- Options:
[A] Architecture Debt — wrong abstractions, missing patterns, coupling issues[B] Code Quality Debt — duplication, complexity, naming, missing types[C] Test Debt — missing tests, flaky tests, untested edge cases[D] Documentation Debt — missing/outdated docs, undocumented APIs[E] Dependency Debt — outdated packages, deprecated APIs, version conflicts[F] Performance Debt — known slow paths, memory issues, unoptimized queries
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 143 lines · 33 tokens per session scan A 447b96080981
tech-debt is a skill published in the GitHub repository frabcd/codex-ai-game-studio (9 stars, last pushed 6d ago), licensed MIT. It adds 33 tokens to every session and 1,361 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to tech-debt, differing in 18 lines, and is treated as a copy.
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