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/v0lka/skills/explorenpx skills add v0lka/skills --skill exploregit clone --depth 1 https://github.com/v0lka/skillsWrote 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/v0lka/skills/explore)<a href="https://agentmods.dev/skills/v0lka/skills/explore"><img src="https://agentmods.dev/badge/skills/v0lka/skills/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 | $0.00080 | $0.06072 |
| Opus 5 | $0.00040 | $0.03036 |
| Sonnet 5 | $0.00016 | $0.01214 |
| Haiku 4.5 | $0.00008 | $0.00607 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 821 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explore → Plan → Implement
This skill is a three-mode workflow. It starts as a thinking partner, transitions into structured planning, and finishes with implementation — all self-contained, no external mode-switching required.
┌───────────┐ ideas ┌───────────┐ approve ┌──────────────┐
│ Explore │ crystallize │ Plan │─────────────▶│Implementation│
│ Mode │────────────▶│ Mode │ │ Mode │
│ │ │ │ │ │
│ thinking, │ │ roadmap │ │ execute │
│ no code │ │ spec │ │ tasks │
└─────┬─────┘ └─────┬─────┘ └──────┬───────┘
▲ │ │
│ unknowns │ revise │ plan
│ emerge │ │ broken
└─────────────────────────┘ │
◀───────────────────────────┘
Mode transitions are driven by the skill itself, not by an agent-level
switch_mode function. The skill announces each transition explicitly
("Entering Plan Mode", "Entering Implementation Mode") and follows the
mode-appropriate rules below.
Mode 1: Explore
Enter explore mode. Think deeply. Visualize freely. Follow the conversation wherever it goes.
IMPORTANT: Explore mode is for thinking, not implementing. You may read files, search code, and investigate the codebase, but you must NEVER write code or implement features. If the user asks you to implement something, remind them that implementation happens in Implementation Mode — after exploration and planning. You MAY offer to enter Plan Mode when ideas crystallize.
This is a stance, not a workflow. There are no fixed steps, no required sequence, no mandatory outputs. You're a thinking partner helping the user explore.
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.
- 4d ago First seen · 821 lines · 80 tokens per session scan A d80efa8bee0c
explore is a skill published in the GitHub repository v0lka/skills (16 stars, last pushed 28d ago), licensed MIT. It adds 80 tokens to every session and 6,072 once invoked, about $0.0004 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.
Other skills, from other repositories
claude-md-improver
Audit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project…
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
Use when evaluating A-share limit-up (涨停板) setups through Chen Hao's sentiment and momentum lens: market emotion cycles, board strength, follow-through, and short-term aggressive momentum trading.
comet-github
将 Comet GitHub 维护请求路由到基于证据的 PR 审阅、Issue 分诊、本地想法收集、CI 诊断或 Issue 实施流程。用户提到 Comet GitHub Issue/PR 但未指定流程，或询问下一步如何处理时使用。.