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 agentmods add skills/rjmurillo/ai-agents/programming-advisornpx skills add rjmurillo/ai-agents --skill programming-advisorgit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/programming-advisor)<a href="https://agentmods.dev/skills/rjmurillo/ai-agents/programming-advisor"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/programming-advisor.svg" alt="Measured on agentmods" 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 | $0.00113 | $0.03780 |
| Opus 5 | $0.00056 | $0.01890 |
| Sonnet 5 | $0.00023 | $0.00756 |
| Haiku 4.5 | $0.00011 | $0.00378 |
Grade A, and why
programming-advisor 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 2d 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 — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Programming Advisor - "Reinventing the Wheel" Detector
Triggers
| Trigger Phrase | Action |
|---|---|
| "should I build X or use a library" | Search internal prior-art first (Step 2a), then external solutions, provide comparison |
| "find existing solutions for X" | Search internal prior-art first (Step 2a), then web search, categorize findings |
| "is there a package for X" | Check existing dependencies first (Step 2a), then search npm/pip/cargo/etc |
| "build vs buy for X" | Tactical: generate cost comparison table; Strategic (>$50K, multi-year, partner/defer options): delegate to buy-vs-build-framework |
| "check if X exists before building" | Run full wheel detection workflow |
| "do we already have X" / "is there existing code for X in this repo" | Search internal prior-art first (leverage/extend), then external |
Core Philosophy
Before writing a single line of code, determine if the wheel already exists. Vibe coding burns tokens, time, and creates maintenance burden. Existing solutions often provide better quality, security patches, and community support.
Process
Step 1: Capture Intent
Extract from user request:
- What: Core functionality needed
- Why: Use case / problem being solved
- Constraints: Language, platform, budget, licensing requirements
Step 2: Search for Existing Solutions
Search internal prior-art FIRST (leverage/extend), then external. The cheapest option is code you already have.
2a. Internal prior-art
Before any web search, check whether the capability already exists in the current repo or org:
- grep the codebase for the capability's keywords and likely symbol names
- if Serena is available, run a symbol search; if Forgetful memory is available, query it
- check existing dependencies (
package.json/requirements.txt/Cargo.toml/go.mod) for a library already pulled in
If an internal implementation exists, recommend Leverage (use as-is) or Extend (adapt it) before proposing a build or an external buy. Internal reuse beats both a new dependency and a rewrite.
What ships with it
5 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.
- 2d ago First seen · 391 lines · 113 tokens per session scan A c921fd24a13d
programming-advisor is a skill published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 113 tokens to every session and 3,780 once invoked, about $0.0006 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 2026-09-03.
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