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 omnigentx/jarvis --skill engineering-principlesgit clone --depth 1 https://github.com/omnigentx/jarvisWrote 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/omnigentx/jarvis/engineering-principles)<a href="https://agentmods.dev/skills/omnigentx/jarvis/engineering-principles"><img src="https://agentmods.dev/badge/skills/omnigentx/jarvis/engineering-principles/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/omnigentx/jarvis/engineering-principles"><img src="https://agentmods.dev/badge/skills/omnigentx/jarvis/engineering-principles.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
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 MCP Rug Pull · line 76 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00029 | $0.00789 |
| Opus 5.5 | $0.00012 | $0.00316 |
| Sonnet 5.5 | $0.00006 | $0.00158 |
| Haiku 4.5 | $0.00003 | $0.00079 |
Grade A, and why
engineering-principles 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engineering Principles
These rules reduce the most common LLM coding mistakes. They override speed — if a rule slows you down, follow it anyway.
1. Think Before Coding
Don't assume. Don't hide confusion. Surface tradeoffs.
- State your assumptions explicitly in the PR/commit message. If uncertain, email the BA or SA — don't guess.
- If the spec admits multiple interpretations, list them and ask. Don't pick silently.
- If a simpler approach exists than what the spec requires, flag it. Push back when warranted.
- If something is unclear, stop and ask. One clarifying email costs less than a rewrite.
2. Simplicity First
Minimum code that solves the problem. Nothing speculative.
- No features beyond the Jira story's acceptance criteria.
- No abstractions for single-use code.
- No "flexibility" or "configurability" that wasn't requested.
- No error handling for scenarios that can't happen (trust internal code + framework guarantees).
- If you write 200 lines and it could be 50, rewrite it.
Self-check: "Would a senior engineer call this overcomplicated?" If yes, simplify.
3. Surgical Changes
Touch only what you must. Clean up only your own mess.
- Don't "improve" adjacent code, comments, or formatting.
- Don't refactor things that aren't broken.
- Match existing style, even if you'd do it differently.
- Unrelated dead code → mention it in the PR description, don't delete it.
When your changes create orphans:
- Remove imports/variables/functions that YOUR changes made unused.
- Don't remove pre-existing dead code unless the story asks for it.
Every changed line should trace directly to the Jira story.
4. Goal-Driven Execution
Define success criteria. Loop until verified.
Before writing code, restate the goal as a verifiable check:
- "Add validation" → "Write tests for invalid inputs, then make them pass" (TDD is mandatory anyway)
- "Fix the bug" → "Write a test that reproduces it, then make it pass"
- "Refactor X" → "Ensure tests pass before AND after, no behavior change"
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 · 80 lines · 29 tokens per session scan A 7b8b840a9007
engineering-principles is a skill published in the GitHub repository omnigentx/jarvis (39 stars, last pushed 4d ago), licensed MIT. It adds 29 tokens to every session and 789 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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