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 DevelopersGlobal/ai-agent-skills --skill surgical-changesgit clone --depth 1 https://github.com/DevelopersGlobal/ai-agent-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/developersglobal/ai-agent-skills/surgical-changes)<a href="https://agentmods.dev/skills/developersglobal/ai-agent-skills/surgical-changes"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/surgical-changes/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/developersglobal/ai-agent-skills/surgical-changes"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/surgical-changes.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 | $0.00036 | $0.00946 |
| Opus 5.5 | $0.00014 | $0.00378 |
| Sonnet 5.5 | $0.00007 | $0.00189 |
| Haiku 4.5 | $0.00004 | $0.00095 |
Grade A, and why
surgical-changes 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 1mo 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Every changed line is a line the reviewer must inspect, a line that could introduce a regression, and a line that will appear in the git blame forever. Unnecessary changes are costly.
AI agents often "improve" adjacent code, reformat files, rename variables for consistency, or delete "dead" code — all without being asked. This creates noisy diffs, unexpected behavior changes, and broken trust.
This skill enforces a hard rule: every changed line must trace directly to the user's request.
When to Use
- Any time you are modifying existing code (not creating new files)
- When your diff is larger than you expected
- When reviewing your own generated changes before presenting them
Process
Step 1: Establish the Change Boundary
- Read the task carefully. Write down exactly which files and functions need to change.
- Draw a mental boundary: "Everything outside this boundary is out of scope."
- List what you will NOT change, even if you'd do it differently:
- Adjacent functions
- Variable naming conventions
- Comment style
- Import order
- Formatting/whitespace (unless fixing a specific bug)
Verify: You can name the specific functions/lines that need to change.
Step 2: Make Only the Required Changes
- Make the changes — and only the changes — within the defined boundary.
- If you notice something wrong outside the boundary:
- Mention it in a comment — don't fix it silently
- Example: "Note: I noticed
fetchUserhas no error handling, but I'm leaving that for a separate PR."
- If your changes made imports/variables/functions unused: remove only those created by YOUR changes. Leave pre-existing dead code alone (unless asked).
Verify: No line changed that wasn't part of the defined scope.
Step 3: Review Your Own Diff
- Read through your diff line by line.
- For each changed line, ask: "Why did I change this?"
- If you can't answer → revert it
- Flag any changes that are purely cosmetic and ask: "Should I include this?"
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.
- 1mo ago First seen · 94 lines · 36 tokens per session scan A bc2fd92ac493
surgical-changes is a skill published in the GitHub repository DevelopersGlobal/ai-agent-skills (211 stars, last pushed 3d ago), licensed MIT. It adds 36 tokens to every session and 946 once invoked, about $0.0001 per session on Opus 5.5. 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.
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