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/bidiche49/claude-conf/explorenpx skills add Bidiche49/claude-conf --skill exploregit clone --depth 1 https://github.com/Bidiche49/claude-confWrote 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/bidiche49/claude-conf/explore)<a href="https://agentmods.dev/skills/bidiche49/claude-conf/explore"><img src="https://agentmods.dev/badge/skills/bidiche49/claude-conf/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 | $0.00018 | $0.00361 |
| Opus 5 | $0.00009 | $0.00180 |
| Sonnet 5 | $0.00004 | $0.00072 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
explore scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Explore #$ARGUMENTS in depth using a structured, parallel approach.
Process
-
Plan (30 seconds max):
- Break the topic into 2-3 specific sub-questions
- Identify what to search: codebase, docs, web, or all
-
Explore (parallel agents):
- Launch 1-2 agents maximum for codebase search
- Launch 1 agent for web/docs if library-specific knowledge needed
- Each agent has a focused question, not a vague "look around"
-
Synthesize:
- Merge findings from all agents
- Identify conflicts or gaps
- Produce a structured report
Report format
Exploration: [topic]
Key findings
- [Finding 1 — with file:line references where applicable]
- [Finding 2]
Architecture / Patterns
- [How the codebase handles this]
Recommendations
- [If the user asked "how should we..." — concrete recommendation]
- [If the user asked "how does..." — no recommendation needed]
Files explored
- path/to/file — [what was found]
Rules
- NEVER explore without a plan — even 30 seconds of planning saves 5 minutes of wandering
- Max 2 parallel agents during explore — more creates context fragmentation
- Always include file:line references — vague answers are worthless
- If the topic is too broad, narrow it and tell the user what you narrowed
- If stuck after 2 minutes: stop exploring, report what you found, ask the user to refine
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 · 53 lines · 18 tokens per session scan A d71599907213
explore is a skill published in the GitHub repository Bidiche49/claude-conf (2 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 361 once invoked, about $0.0001 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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goal
Run a large or unfamiliar goal through the full ballast pipeline — mobilize what you already hold, terrain scan, full skeleton, atomic foundation learning with verification, then build from bedrock to a verified done. Use when the user hands over a big goal, enters a new field, or asks to learn X in order to achieve Y.
report
Read the delivery log and say which rules actually fire, which never have, and what to prune or fix. Use when the user asks whether ballast is doing anything, wants to clean up their rule catalog, or on a periodic review.
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eval-harness
Assessment-driven development — Quantify code generation quality with pass@k / pass^k metrics, automatically scored by Grader.