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 randommonicle/claude-skills --skill live-data-surgerygit clone --depth 1 https://github.com/randommonicle/claude-skillsWrote 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/randommonicle/claude-skills/live-data-surgery)<a href="https://agentmods.dev/skills/randommonicle/claude-skills/live-data-surgery"><img src="https://agentmods.dev/badge/skills/randommonicle/claude-skills/live-data-surgery/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/randommonicle/claude-skills/live-data-surgery"><img src="https://agentmods.dev/badge/skills/randommonicle/claude-skills/live-data-surgery.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00136 | $0.00718 |
| Opus 5 | $0.00068 | $0.00359 |
| Sonnet 5 | $0.00027 | $0.00144 |
| Haiku 4.5 | $0.00014 | $0.00072 |
Grade A, and why
live-data-surgery 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 11d 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Live-data surgery
Six incidents around ad-hoc destructive operations: a sweep whose self-check under-claimed, a committed cleanup that would have deleted the demo data because "Smoke" was its name, over a thousand leaked rows from an earlier partial pass, and a bulk delete rolled back wholesale by one surviving RESTRICT child. safe-smokes governs tests; this skill governs the one-off surgery — same danger, different trigger surface. A warn-and-log hook (hooks/sql-surgery-warn.mjs) backstops this skill by logging destructive SQL it sees.
The protocol, in order
- Read-only inventory first. Count, sample, and walk the FK graph of what the predicate matches — as a result grid you read, not NOTICEs that scroll away.
- Check the markers sit on disposable rows. A name is not a disposability proof: "Smoke" turned out to be the demo dataset. Verify by content, not label.
- BEGIN … ROLLBACK dry run. The transaction still returns the report rows, so you see
exactly what would happen at zero risk. Script version: dry-run by default, mutate only
under an explicit
--apply. - Complement-count proof with NULL-collapsed predicates. Three-valued SQL makes
NOT (x = y)lie on NULLs; prove kept + deleted = total with predicates that collapse NULL explicitly. - Self-check re-runs EVERY predicate. A sweep's final assertion must re-run each seed predicate individually — a combined check once under-claimed and left residue attributed to success.
- FK order and atomicity. Delete children before parents; know that one surviving RESTRICT child rolls back an entire atomic bulk delete — which is a feature, if you watch for it.
- Gate tamper-evidence resets. Anything that resets audit trails, sequence baselines, or tamper-evidence gets its own explicit confirmation, never rides along.
What this skill does not do
It does not apply inside test harnesses — safe-smokes owns test hygiene, including flip-and-restore and teardown assertions. It does not authorise the surgery; it assumes the decision is made and makes the execution provable.
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.
- 11d ago First seen · 48 lines · 0 tokens per session scan A ae582bd8dfd8
live-data-surgery is a skill published in the GitHub repository randommonicle/claude-skills (23 stars, last pushed 4d ago), licensed Apache-2.0. It adds 136 tokens to every session and 718 once invoked, about $0.0007 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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