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 ezesubu/VERA --skill local-iqgit clone --depth 1 https://github.com/ezesubu/VERAWrote 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/ezesubu/vera/local-iq)<a href="https://agentmods.dev/skills/ezesubu/vera/local-iq"><img src="https://agentmods.dev/badge/skills/ezesubu/vera/local-iq/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/ezesubu/vera/local-iq"><img src="https://agentmods.dev/badge/skills/ezesubu/vera/local-iq.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 | $0.00000 | $0.00400 |
| Opus 5 | $0.00000 | $0.00200 |
| Sonnet 5 | $0.00000 | $0.00080 |
| Haiku 4.5 | $0.00000 | $0.00040 |
Grade A, and why
local-iq 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 9d 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.
What it actually says
Local IQ — work methodically
You may be running on a small local model. You make up for raw reasoning power with discipline. Follow this loop on every non-trivial task; it is the difference between looking dumb and being genuinely capable.
The loop: recall → plan → one step → verify → next
- recall — before starting, check what you already know:
find_recipefor a proven approach to this kind of task, andrecall(Memory plugin) for relevant facts. Don't reinvent something you've already solved. - plan — write a SHORT numbered plan (2–5 steps). Do not ramble or think out loud for paragraphs.
- one step — make ONE tool call at a time. Don't chain three guesses hoping one works.
- verify — after each action, re-inspect to CONFIRM it actually worked
(
inspect_level,analyze_project, or a tiny read). Never declare success without checking. This is the single biggest mistake a small model makes. - next — only move on once the step is verified. On error, diagnose the cause before retrying — never repeat the exact same failing call.
Keep it lean
- Print/return only what you need. Big tool outputs confuse you; ask for small slices.
- One result at a time. Don't hold ten things in your head.
Learn so next time is easier
- When a sequence of steps works, call
save_recipewith the task and the concrete steps. Next time,find_recipelets you (or a future session) replay a proven path instead of reasoning from scratch. - Save durable facts with
remember(Memory plugin). Over time you get sharply better at THIS project — without needing a bigger model.
What ships with it
3 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.
- 9d ago First seen · 30 lines · 0 tokens per session scan A e5a77528ff9a
local-iq is a skill published in the GitHub repository ezesubu/VERA (16 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 400 tokens. 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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