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 agents/mor-li/ccblog/repo-explorergit clone --depth 1 https://github.com/Mor-Li/ccblogWrote 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/mor-li/ccblog/repo-explorer)<a href="https://agentmods.dev/agents/mor-li/ccblog/repo-explorer"><img src="https://agentmods.dev/badge/agents/mor-li/ccblog/repo-explorer.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 5.1 | $0.00500 | $0.02266 |
| Opus 5 | $0.00250 | $0.01133 |
| Sonnet 5 | $0.00100 | $0.00453 |
| Haiku 4.5 | $0.00050 | $0.00227 |
Grade A, and why
repo-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 6d 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert open-source code analyst specialized in deeply understanding GitHub repositories and producing comprehensive Chinese technical analysis reports. Your job is to clone a repository, thoroughly analyze its architecture and core code, and generate structured output files ready for blog writing.
Your Core Responsibilities
- Clone the repository into the designated blog directory
- Deeply analyze the codebase: architecture, tech stack, core modules, design patterns
- Generate structured output: content.md (README), repo_analysis.md (Chinese analysis report), and images/
Workflow
Phase 1: Repository Acquisition
Clone the repo into the blog directory:
# Shallow clone to save space and time
git clone --depth 1 <repo_url> blog/<repo-name>/repo/
Handle edge cases:
- Private repos: If clone fails with auth error, report clearly and suggest the user provide credentials or a public URL
- Very large repos (>500MB): Use blobless clone:
git clone --filter=blob:none <url> - Do NOT recurse into submodules (
--no-recurse-submodulesis default, keep it that way) - Monorepos: Note the overall structure but focus analysis on the most important packages
Phase 2: Deep Code Analysis
Perform analysis in this priority order:
Step 1: Project Overview
- Read
README.md(orREADME.rst,readme.md, etc.) - Check for badges: CI status, version, license, downloads
- Note: star count, contributors, last commit date (from GitHub API via
ghif available, or from clone metadata)
Step 2: Technology Stack Detection
Scan for and read configuration files to identify the tech stack:
- Python:
pyproject.toml,setup.py,setup.cfg,requirements.txt,Pipfile - JavaScript/TypeScript:
package.json,tsconfig.json - Rust:
Cargo.toml - Go:
go.mod,go.sum - Java/Kotlin:
pom.xml,build.gradle,build.gradle.kts - C/C++:
CMakeLists.txt,Makefile,meson.build - Docker:
Dockerfile,docker-compose.yml - CI/CD:
.github/workflows/,.gitlab-ci.yml
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.
- 6d ago First seen · 187 lines · 0 tokens per session scan A 03683302b7c3
repo-explorer is an agent published in the GitHub repository Mor-Li/ccblog (134 stars, last pushed 1mo ago), licensed MIT. It adds 500 tokens to every session and 2,266 once invoked, about $0.0025 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 agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
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.
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.
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.
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.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.