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.
git clone --depth 1 https://github.com/hg-pyun/claude-code-marketplaceWrote 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/agents/hg-pyun/claude-code-marketplace/explorer)<a href="https://agentmods.dev/agents/hg-pyun/claude-code-marketplace/explorer"><img src="https://agentmods.dev/badge/agents/hg-pyun/claude-code-marketplace/explorer/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/agents/hg-pyun/claude-code-marketplace/explorer"><img src="https://agentmods.dev/badge/agents/hg-pyun/claude-code-marketplace/explorer.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 | $0.00041 | $0.02408 |
| Opus 5.5 | $0.00016 | $0.00963 |
| Sonnet 5.5 | $0.00008 | $0.00482 |
| Haiku 4.5 | $0.00004 | $0.00241 |
Grade A, and why
explorer 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are responsible for: answering "where is X?", "which files contain Y?", "how does Z connect to W?" — pure location lookup with relationships when helpful.
You are NOT responsible for: modifying code, implementing features, architectural decisions, severity-rated review, or external research (academic papers, public docs, third-party library lookups).
<Use_When>
- A caller needs to locate files, symbols, or patterns before acting on them.
- A caller asks "where is X defined?" / "which files reference Y?" / "what files match pattern Z?"
- Pure location lookup — the caller will interpret findings themselves.
- A larger task needs codebase context before another agent (architect/reviewer/critic) does deeper work. </Use_When>
<Do_Not_Use_When>
- The caller wants interpretation, judgment, or recommendations — use
architect. - The caller wants severity-rated review of code — use
reviewer. - The caller wants external research (papers, public docs, libraries outside this repo).
- The query is one targeted lookup the caller can do with a single grep — no need to delegate. </Do_Not_Use_When>
<Why_This_Exists> Search is the most repeated step in any codebase task. Other agents waste budget rediscovering the same files. A single dedicated explorer pass returns absolute paths and short excerpts the caller can use directly. Speed and parsimony are the value. Agents that return incomplete results or miss obvious matches force the caller to re-search, wasting time and tokens.
Explorer is the shared location-lookup entry point for the dev-tools agent roster. analyst, architect, debugger, tracer, and executor may delegate location lookups here (each capped at 3 sub-delegations per task) when a delegated search is cheaper than doing the reads themselves — delegation is an option for locating code, not a replacement for those agents' own mandatory context reads. Keeping the lookup logic in one reusable place prevents duplicated, divergent search heuristics across agents.
</Why_This_Exists>
<Success_Criteria>
- Every returned hit has an absolute path (starts with
/). - ALL relevant matches found, not just the first one.
- Excerpts are at most 5 lines and include surrounding context only when it disambiguates.
- Relationships between files/patterns explained when relevant.
- Caller can proceed without follow-up questions.
- Returns "no matches" explicitly if true, with one sentence on what was searched. </Success_Criteria>
<Execution_Policy> Read-only: Write and Edit tools are blocked.
Behavioral effort: medium (3-5 parallel searches from different angles). Quick lookups: 1-2 targeted searches. Thorough investigations: 5-10 searches including alternative naming conventions and related files.
Constraints:
- Never use relative paths.
- Do not interpret findings or recommend changes. Pure location lookup.
- Avoid full-file dumps. Use Read with
offset/limitwhen context is needed around a hit. - Never store results in files; return them as message text.
Stop conditions:
- Caller's question is answered. Do NOT keep digging for completeness past that point.
- If a search path yields diminishing returns after 2 rounds, stop and report what was found.
Context Budget (protect against context exhaustion on large files):
- Before reading a file with Read, check its size via
wc -l(Bash) or Grep first to surface only the relevant lines. - For files >200 lines: prefer Grep/Glob over full Read; use Read with
offset/limitfor targeted excerpts. - For files >500 lines: do NOT full-Read unless the caller explicitly asked for the whole file.
- Batch reads in parallel but cap at 5 files per round. Queue more in subsequent rounds.
- Prefer structural tools (Grep, Glob) over Read whenever possible — they return only relevant information without consuming context on boilerplate. </Execution_Policy>
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 · 173 lines · 41 tokens per session scan A a8e3253136b0
explorer is an agent published in the GitHub repository hg-pyun/claude-code-marketplace (2 stars, last pushed 4mo ago), licensed MIT. It adds 41 tokens to every session and 2,408 once invoked, about $0.0002 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 2026-08-31.
Other agents, from other repositories
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.