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/arcasilesgroup/ai-engineering/ai-explorenpx skills add arcasilesgroup/ai-engineering --skill ai-exploregit clone --depth 1 https://github.com/arcasilesgroup/ai-engineeringWrote 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/arcasilesgroup/ai-engineering/ai-explore)<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-explore"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-explore.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 | $0.00115 | $0.00707 |
| Opus 5 | $0.00057 | $0.00353 |
| Sonnet 5 | $0.00023 | $0.00141 |
| Haiku 4.5 | $0.00012 | $0.00071 |
Grade A, and why
ai-explore 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 5d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Read this repository and answer
What it produces
An answer anchored to real paths. Every claim points at file:line, or it is marked as a
guess.
Steps
-
Match the depth to the question, not to a flag. "Where is X" gets a path and a sentence. "How does this work" gets the flow. "Onboard me" gets a tour, and a tour is longer than five sentences by definition.
-
Match the words to who is asking. Somebody who does not code gets what the thing does and what it costs them when it breaks, with the file paths kept as evidence rather than as the answer; somebody who does gets the path first. Ask which if the question does not say, and never answer a business question with a call graph.
-
Find the real entry point before reading anything else. Working outward from the wrong file produces a confident answer about the wrong subsystem.
-
Follow one real path end to end and say what happens at each hop. Never summarise a flow from file names alone — that is the single most common way this goes wrong, and it reads exactly like a correct answer.
-
When the shape is the answer, draw it. Under 70 columns, and every box is a real file that exists:
settings.json ──> chain.py ──> self_protect ──> exit 2 └───────> loop_guard -
Explain what is here, not the pattern in general. If a textbook name applies, one clause is enough; the reader came for this codebase.
-
Name the pitfall by pointing at a line in this repository. A generic warning helps nobody; "this returns None on line 84 and the caller does not check" does.
-
If the answer is "it does not exist here", say that in the first sentence.
Done when
- Every claim has a path, or is explicitly marked as unverified.
- The person could reach your conclusion by opening the files you named, in that order.
- Nothing was changed. This skill reads; it never writes.
What this is not
Not a design review, not a refactor, and not an opinion about quality. If you spot something genuinely dangerous, say it in one line at the end and move on.
What ships with it
1 file 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.
- 5d ago First seen · 62 lines · 115 tokens per session scan A ea27717b2495
ai-explore is a skill published in the GitHub repository arcasilesgroup/ai-engineering (54 stars, last pushed 3d ago), licensed Apache-2.0. It adds 115 tokens to every session and 707 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 2026-08-30.
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