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/yohn1985/jarvisbot/discovernpx skills add yohn1985/jarvisbot --skill discovergit clone --depth 1 https://github.com/yohn1985/jarvisbotWrote 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/yohn1985/jarvisbot/discover)<a href="https://agentmods.dev/skills/yohn1985/jarvisbot/discover"><img src="https://agentmods.dev/badge/skills/yohn1985/jarvisbot/discover.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 | $0.00039 | $0.00435 |
| Opus 5 | $0.00019 | $0.00217 |
| Sonnet 5 | $0.00008 | $0.00087 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade A, and why
discover 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 4d 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
discover
The heart of Jarvis: land on a machine, look around, and write down what you learned so it becomes durable understanding instead of a one-off glance.
SCAN (pure Python/subprocess) → bounded raw facts about the host + what it can see
ORGANIZE (LLM) → the brain turns raw facts into a clear, factual document
PERSIST → workspace/discovery/<host>-<ts>.md
Scanning is degrade-safe (any missing tool is skipped, never crashes). The organizing step runs on Jarvis's configured brain (claude/codex/ollama-cloud) — it must not invent anything not in the facts.
Usage
./install.sh skill run discover # discover this host, write the doc
./install.sh skill run discover --print # also print the document
Output
A markdown document describing the machine's role, services + ports, networking (interfaces,
routes, neighbours/other devices), storage, containers, and an "open questions / worth
investigating" list. Saved under workspace/discovery/.
Roadmap (next increments)
- Network sweep: enumerate other devices/ports on the local subnet (consent-gated).
- Persist findings into the
knowledge/knowledge_mapmemory tables (staleness drives curiosity). - Loop integration: run on the curiosity rung so Jarvis keeps its understanding fresh on its own.
What ships with it
2 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.
- 4d ago First seen · 39 lines · 39 tokens per session scan A f07386cb16b3
discover is a skill published in the GitHub repository yohn1985/jarvisbot (1 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 435 once invoked, about $0.0002 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 2026-08-31.
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