Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/yonatangross/orchestkitnpx agentmods add commands/yonatangross/orchestkit/exploreWrote 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/commands/yonatangross/orchestkit/explore)<a href="https://agentmods.dev/commands/yonatangross/orchestkit/explore"><img src="https://agentmods.dev/badge/commands/yonatangross/orchestkit/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/commands/yonatangross/orchestkit/explore"><img src="https://agentmods.dev/badge/commands/yonatangross/orchestkit/explore.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00068 | $0.03699 |
| Opus 5.5 | $0.00027 | $0.01480 |
| Sonnet 5.5 | $0.00014 | $0.00740 |
| Haiku 4.5 | $0.00007 | $0.00370 |
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 today.
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 — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto-generated from skills/explore/SKILL.md
Source: https://github.com/yonatangross/orchestkit
Codebase Exploration
Host-neutral workflow. Invoke by skill name (explore). Claude Code slash routing, YAML hook loaders, and .claude/chain live in skills/explore/references/claude-code.md.
Multi-angle codebase exploration using 3-5 parallel agents.
🎯 Quick Start
explore authentication
Opus 5.5: Exploration agents use native adaptive thinking for deeper pattern recognition across large codebases.
STEP -0.5: Effort-Aware Agent Scaling (CC 2.1.120+)
Read $CLAUDE_EFFORT to scale exploration depth before any other decision.
# CC 2.1.120+ env var; explicit --effort= overrides
EFFORT = os.environ.get("CLAUDE_EFFORT")
for token in "$ARGUMENTS".split():
if token.startswith("--effort="):
EFFORT = token.split("=", 1)[1]
EFFORT = EFFORT or "high" # default
| Effort | Agent count | Phases | Time |
|---|---|---|---|
low |
1 (structure-only) | 1, 2, 8 | ~1 min |
medium |
2 (structure + data flow) | 1, 2, 3 (subset), 8 | ~3 min |
high (default) |
4 (full parallel team) | 1–8 | ~6 min |
xhigh (Opus 5) |
5 (+ uncertainty pass on health scores) | 1–8 + caveats | ~8 min |
Override gate: if the user passes --effort=high explicitly while $CLAUDE_EFFORT is low, the flag wins. doctor warns only when xhigh is configured on a model in its XHIGH_UNSUPPORTED_PREFIXES table.
STEP 0: Verify User Intent with AskUserQuestion
BEFORE creating tasks, clarify what the user wants to explore:
AskUserQuestion(
questions=[{
"question": "What aspect do you want to explore?",
"header": "Focus",
"options": [
{"label": "Full exploration (Recommended)", "description": "Code structure + data flow + architecture + health assessment"},
{"label": "Quick scan", "description": "Find relevant files + structure, skip deep analysis"},
{"label": "Data flow", "description": "Trace how data moves through the system"},
{"label": "Architecture patterns", "description": "Identify design patterns and integrations"}
],
"multiSelect": false
}]
)
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.
- today Changed e36bf295fcd3
- 5d ago Changed · +6 lines 66112ee628e0
- 17d ago Changed de12d1b1ef0c
- 21d ago Changed 466aedc22cb0
- 23d ago Changed e53dea942454
- 24d ago Changed d78850b4de44
- 1mo ago Changed · +2 lines 3b65bb744282
- 1mo ago Changed f172eeff6eca
- 1mo ago First seen · 319 lines · 68 tokens per session scan A cb653bb2f630
explore is a command published in the GitHub repository yonatangross/orchestkit (295 stars, last pushed today), licensed MIT. It adds 68 tokens to every session and 3,699 once invoked, about $0.0003 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.
Other commands, from other repositories
bug
Reproduce then TDD-fix a ready-for-agent bug ticket in this checkout. Web bugs get a browser repro first.
pn-distill
Remove content, sections, and features that don't earn their place — information architecture reduction. Use when there's too much stuff on the page. For visual decoration reduction, use pn-quieter.
distil-shadow
Decision-equivalence report — did compression preserve your agent's next action?
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.