Borrowing it
Nothing to install: this file belongs to tbhb/vale-ai-tells. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tbhb/vale-ai-tells/main/.claude/skills/codex-rebase/SKILL.mdgit clone --depth 1 https://github.com/tbhb/vale-ai-tellsWrote 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/tbhb/vale-ai-tells/codex-rebase)<a href="https://agentmods.dev/skills/tbhb/vale-ai-tells/codex-rebase"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/codex-rebase/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.
<a href="https://agentmods.dev/skills/tbhb/vale-ai-tells/codex-rebase"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/codex-rebase.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Tool Misuse · line 121 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Excessive Agency · line 67 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.
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 | $0.00109 | $0.01828 |
| Opus 5 | $0.00055 | $0.00914 |
| Sonnet 5 | $0.00022 | $0.00366 |
| Haiku 4.5 | $0.00011 | $0.00183 |
Grade A, and why
codex-rebase 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.
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.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rebase workflow
Move the branch onto its base, then establish that what came out is right.
Codex doesn't provide a skill-scoped command hook. Use only the scripts named here to pin the rebase settings and check conflict markers before continuing. The continuation script also proves an empty skip. Never use a bare stash pop, start the rebase by hand, or force-push without a lease.
Preflight
Run bash .agents/skills/codex-rebase/scripts/preflight.sh.
Step 0: open the task list
Create these with update_plan, keeping exactly one item in_progress at a time.
- Choose the base
- Settle the working tree
- Start the rebase
- Resolve whatever it stops on
- Verify the result
- Report
Preflight reporting a merge or cherry-pick in progress stops everything. Say what's in the way and hand back. A rebase already in progress is the other case, and that one resumes at step 4.
Step 1: choose the base
Preflight computed this under == rebase base ==. Take its recommendation.
- Local default branch carries everything the remote has, so rebase onto the local branch.
- Local default branch sits behind the remote, so rebase onto
origin/<default>and skip the stale local copy.
The commit skill's preflight makes the same decision, and both reach the same answer. Where the operator names a different base, use theirs and say why it differs.
Nothing to replay means nothing to do. Say so and stop.
Step 2: settle the working tree
--autostash handles a dirty tree, and start-rebase.sh passes it. It scopes the save to this rebase and never touches the shared stash stack, which is what makes it the sanctioned form here.
The stashed work sits outside the worktree while you resolve a conflict, so nothing you see there reflects it. It can also conflict on the way back once the replay finishes. If that durability isn't enough, stop and let the operator settle the worktree before starting. Don't invent a temporary commit or reset sequence inside this workflow.
What ships with it
7 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.
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.
- 10d ago First seen · 134 lines · 109 tokens per session scan A 09934c8ac244
codex-rebase is a skill published in the GitHub repository tbhb/vale-ai-tells (91 stars, last pushed today), licensed MIT. It adds 109 tokens to every session and 1,828 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
anti-slop
Remove AI slop from any voice-bearing prose — original posts, threads, articles, long-form, emails, docs, READMEs, marketing copy, bios, scripts. Use when drafting text meant to sound like a specific person or brand, when rewriting text that reads generic, corporate, or AI-generated, or when asked to humanize…
kill-slop
Audit a file or draft for AI slop and off-voice lines against the author's bound voice, report findings with in-voice swaps, then apply approved fixes. Use when the user says "kill slop", "/kill-slop [file]", "find the slop in this", "audit this for slop", or wants a deck, article, page, or draft cleaned to sound like…
humanizer
Humanize and de-slop AI-sounding prose while preserving meaning, specific detail, and genuine human quirks. When a voice sample or style profile is available, rewrite in that writer's actual voice. Remove recurring AI tells such as inflated significance, stock vocabulary, uniform rhythm, excessive hedging, formulaic…
authenticity-check
Score how authentically text reads as a real human author's work, flag spans that read as AI-generated, AI-templated, or generically derivative, and run a separate read-only scan for suspicious Unicode provenance carriers. Return an authenticity band, a 0-100 score, provenance signals, and span-level reasons. Use when…
ai-slop-detector
Universal prose audit. Scores writing on TWO axes — AI-Slop (does this read like AI wrote it?) and Comprehension (can a fresh reader follow this?). Use PROACTIVELY as a mandatory final QA pass on ANY prose generated for humans to read — every email (internal or external), proposal, report, status update, blog post…
humanizer-czech
Odstraň znaky AI-generovaného psaní z českého textu. Použij při editaci nebo revizi textu, aby zněl přirozeněji a lidštěji. Detekuje a opravuje 27 vzorců včetně: nafouklého významu, propagačního jazyka, anglického slovosledu, kalků, nominalizace, monotónního rytmu, nadužívání spojek, typických českých AI klišé…