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/daffy0208/ai-dev-standards/exploregit clone --depth 1 https://github.com/daffy0208/ai-dev-standardsWhat 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 | $0.00000 | $0.02329 |
| Opus 5 | $0.00000 | $0.01164 |
| Sonnet 5 | $0.00000 | $0.00466 |
| Haiku 4.5 | $0.00000 | $0.00233 |
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 2d 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 — 546 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explore Agent
Fast, configurable codebase exploration agent for understanding project architecture and structure.
Overview
The Explore Agent is optimized for:
- Initial codebase assessment
- Architecture understanding
- Pattern discovery
- Rapid familiarization
Key Feature: Three thoroughness modes (quick, medium, very thorough)
Thoroughness Modes
Quick Mode
Speed: Fast (seconds to minutes) Depth: Surface-level overview
Best For:
- Quick sanity checks
- Initial repository assessment
- Finding specific patterns
- High-level architecture overview
What It Does:
- Scans directory structure
- Identifies main technologies
- Maps key files and folders
- Generates quick summary
Example:
Task: Get overview of React project structure
Mode: Quick
Time: 30 seconds
Output: Directory tree, tech stack, entry points
Medium Mode (Default)
Speed: Moderate (5-15 minutes) Depth: Balanced exploration
Best For:
- General codebase exploration
- Understanding project organization
- Identifying major components
- Balanced depth vs. speed
What It Does:
- Comprehensive directory scan
- File content sampling
- Dependency analysis
- Pattern identification
- Architecture mapping
Example:
Task: Understand authentication flow
Mode: Medium
Time: 10 minutes
Output: Auth components, API endpoints, data flow, dependencies
Very Thorough Mode
Speed: Slow (30+ minutes) Depth: Deep, comprehensive analysis
Best For:
- Complete system understanding
- Pre-refactoring analysis
- Security audits
- Documentation generation
- Complex system mapping
What It Does:
- Reads all relevant files
- Deep dependency analysis
- Cross-reference mapping
- Pattern correlation
- Comprehensive reporting
Example:
Task: Map entire microservices architecture
Mode: Very Thorough
Time: 45 minutes
Output: Complete service map, API contracts, data flows, dependencies
When to Use Explore Agent
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.
- 2d ago First seen · 546 lines · 0 tokens per session scan A 970c38e65c19
explore is an agent published in the GitHub repository daffy0208/ai-dev-standards (36 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,329 tokens. 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.
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