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 juicesharp/rpiv-mono --skill exploregit clone --depth 1 https://github.com/juicesharp/rpiv-monoWrote 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/juicesharp/rpiv-mono/explore)<a href="https://agentmods.dev/skills/juicesharp/rpiv-mono/explore"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/explore/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/juicesharp/rpiv-mono/explore"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/explore.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00089 | $0.04288 |
| Opus 5.5 | $0.00036 | $0.01715 |
| Sonnet 5.5 | $0.00018 | $0.00858 |
| Haiku 4.5 | $0.00009 | $0.00429 |
Grade A, and why
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 2mo 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 — 398 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explore
You are tasked with analyzing solution options for new features or changes by invoking parallel skills and synthesizing their findings into actionable recommendations optimized for design consumption.
Input
$ARGUMENTS — feature/change description, optionally with paths to tickets or research docs.
Metadata
node "${SKILL_DIR}/../_shared/now.mjs"
echo
node "${SKILL_DIR}/../_shared/git-context.mjs"
Copy values verbatim — do not reformat the timezone offset.
Flow
- Input → 2. Generate candidates → 3. Candidate checkpoint → 4. Per-candidate fit → 5. Synthesize → 6. Metadata → 7. Write doc → 8. Present → 9. Follow-ups
The final artifact feeds design.
Steps
Step 1: Input Handling
-
No argument provided — respond with:
I'm ready to research solution options. Please provide: - What feature/change you want to explore - Any requirements or constraints you know about - Reference to relevant ticket or research documents if available I'll analyze the current codebase, generate solution options, and provide recommendations.Then wait for the user's request.
-
Read any files mentioned — tickets, research docs, related artifacts:
- Read them FULLY first using the Read tool WITHOUT limit/offset parameters
- Read these files in main context before invoking skills
- Extract requirements, constraints, and goals
- Identify what problem we're solving
Step 2: Generate Candidates and Dimensions
Generate 2–4 named candidates from three sources, then merge into one shortlist:
- Ecosystem scan — spawn
web-search-researcherfor any topic where the candidate space includes external libraries, frameworks, or services. Prompt it to return 2–4 named options with one-line "what it is" + canonical doc link per option. Skip only when the topic is wholly internal (e.g., "how to organize this service layer") and the orchestrator's design-space enumeration plus the user shortlist already cover the space. - Design-space enumeration — orchestrator names abstract shapes from first principles when applicable (pub/sub vs direct-call vs event-bus; sync vs async; manual mapping vs auto-mapper). One-line "what it is" per shape.
- User shortlist — if the user pre-named candidates in the entry prompt ("compare TanStack Query vs SWR"), include those verbatim.
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.
- 2mo ago First seen · 398 lines · 89 tokens per session scan A bce36efe3303
explore is a skill published in the GitHub repository juicesharp/rpiv-mono (934 stars, last pushed 6d ago), licensed MIT. It adds 89 tokens to every session and 4,288 once invoked, about $0.0004 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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