maintenance-pass

maintenance-pass is a skill for Codex from uchicago-dsi/ai-sci-skills. It costs 83 tokens per session (3,009 once invoked), scanned A, original, MIT.

A workflow for safely cleaning up a codebase, including removing dead code, old scripts, duplicate implementations, and stale configuration.

In plain words
What is it for?
Use it for maintenance or cleanup passes, dead-code removal, duplication reduction, vestige pruning, and trimming excessive lines of code.
Why use it?
It helps reduce maintenance work while limiting unnecessary changes and protecting code that still has a purpose.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions CLAUDE.md; mentions subagents; mentions AGENTS.md.

Good fit Use it for maintenance or cleanup passes, dead-code removal, duplication reduction, vestige pruning, and trimming excessive lines of code.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/uchicago-dsi/ai-sci-skills/maintenance-pass
Install

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.

Any agent
npx skills add uchicago-dsi/ai-sci-skills --skill maintenance-pass
Clone the repo
git clone --depth 1 https://github.com/uchicago-dsi/ai-sci-skills

Made for: Codex.

Wrote 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.

agentmods badge for maintenance-pass

README.md
[![agentmods](https://agentmods.dev/badge/skills/uchicago-dsi/ai-sci-skills/maintenance-pass/github.svg)](https://agentmods.dev/skills/uchicago-dsi/ai-sci-skills/maintenance-pass)
Your own site
<a href="https://agentmods.dev/skills/uchicago-dsi/ai-sci-skills/maintenance-pass"><img src="https://agentmods.dev/badge/skills/uchicago-dsi/ai-sci-skills/maintenance-pass/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for maintenance-pass

Your own site · 80×15
<a href="https://agentmods.dev/skills/uchicago-dsi/ai-sci-skills/maintenance-pass"><img src="https://agentmods.dev/badge/skills/uchicago-dsi/ai-sci-skills/maintenance-pass.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,009 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 119
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00083 $0.03009
Opus 5 $0.00042 $0.01504
Sonnet 5 $0.00017 $0.00602
Haiku 4.5 $0.00008 $0.00301

Measured 10d ago against content hash ac6d02cc264b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

maintenance-pass 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 10d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/maintenance_inventory.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/maintenance-pass/SKILL.md · 188 lines

How it starts

The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Maintenance Pass

Optimize For Maintenance Yield

Prioritize the safest change with the largest maintenance payoff. Delete or simplify code only when evidence supports it. Refactor only when it materially reduces duplication, clarifies ownership, removes a failed path, or protects an important contract. Do not move code around for aesthetics.

Use this rough ranking:

maintenance yield = impact * confidence * stale_touch_signal / blast_radius

Treat time since last git touch as a triage signal, not proof. The relevant metric is the most recent commit that changed a path, not when the file was created. Code whose latest git touch was a long time ago is more likely to be a vestige, duplicated old path, or stale interface, but stable core infrastructure can also be old and correct.

Start With Evidence

  1. Read local repo instructions first: AGENTS.md, CLAUDE.md, README.md, nearby runbooks, and provenance notes tied to the target area.
  2. Check the worktree: git status --short --untracked-files=all. Never revert unrelated user changes. Avoid destructive cleanup in a dirty worktree unless the user explicitly scopes it.
  3. Establish stable baselines:
git ls-files '*.py' | wc -l
git ls-files '*.py' | xargs wc -l | tail -n 1
  1. Build a least-recently-touched candidate list from tracked files before choosing a theme. Prefer files and directories whose most recent git commit touch is old, especially when they are scripts, one-off analyses, retired mechanism code, stale configs, duplicate helpers, or docs for old paths. Use git log -1 --format='%ct %cs %h' -- <path> or the inventory helper's least-recently-touched section. Do not use last-touch age alone to delete stable package owners, tests, schemas, or public APIs.
  2. If the user gives a target LOC change, treat it as a stopping target, not a quota. Aim for the target with the safest high-yield changes first, but stop short when the next candidate has weak evidence or excessive blast radius. Do not pad the diff with formatting, moves, or speculative rewrites to hit the number.
  3. Establish a pre-pass commit boundary before editing without creating empty commits. If the worktree is clean, record the current HEAD as the starting boundary instead of making an empty checkpoint. If the worktree is dirty, do not silently commit unrelated or user-owned changes; either commit only already-approved scoped changes as a real pre-pass checkpoint, or record the current HEAD plus the dirty status as the boundary. If the user explicitly asks for before/after commits but there is nothing real to checkpoint before the pass, report that the starting boundary is the existing HEAD; do not make an empty commit.
  4. Optionally run the bundled inventory helper from the repo root:

Read the full file on GitHub · 188 lines

Files

What ships with it

2 files 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.

Changes

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.

  1. 10d ago First seen · 188 lines · 83 tokens per session scan A ac6d02cc264b

Subscribe to this mod's changes

maintenance-pass is a skill published in the GitHub repository uchicago-dsi/ai-sci-skills (17 stars, last pushed yesterday), licensed MIT. It adds 83 tokens to every session and 3,009 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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