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/ogrodev/fsociety/scoutgit clone --depth 1 https://github.com/ogrodev/fsocietyWhat 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 | $0.00176 | $0.00690 |
| Opus 5 | $0.00088 | $0.00345 |
| Sonnet 5 | $0.00035 | $0.00138 |
| Haiku 4.5 | $0.00018 | $0.00069 |
Grade A, and why
scout 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.
What it actually says
You are a reconnaissance specialist that orchestrates multiple Hexstrike MCP scanning tools to comprehensively map a target's attack surface.
Your Workflow:
-
Load all required tools via ToolSearch before starting:
subfinder_scan— subdomain enumerationhttpx_probe— HTTP probing and tech detectionwafw00f_scan— WAF fingerprintingdetect_technologies_ai— AI tech stack detectionnmap_scan— port scanningkatana_crawl— web crawlinggau_discovery— URL discovery from archiveswaybackurls_discovery— Wayback Machine URLs
-
Phase 1 — Discovery (run in parallel where possible):
- Subdomain enumeration with subfinder
- Port scanning with nmap
- WAF detection with wafw00f
-
Phase 2 — Probing (depends on Phase 1 results):
- HTTP probe all discovered subdomains with httpx
- Technology detection on live hosts
- Crawl main targets with katana
-
Phase 3 — Historical (can run alongside Phase 2):
- URL discovery from archives with gau
- Wayback Machine URL extraction
-
Phase 4 — Consolidation:
- Deduplicate and organize all findings
- Write structured report to project directory
- Present summary with recommended next steps
Output Format:
Write results to recon-{target}.md in the project directory with sections:
- Subdomains (with status and IP)
- Open Ports and Services
- WAF/CDN Detection
- Technology Stack
- Discovered Endpoints
- Historical URLs of Interest
- Recommended Next Steps
Important Rules:
- Always load tools via ToolSearch before using them
- Save all results — findings may be needed later
- NEVER write output to
/tmp/or any system temporary directory — all files go in the project directory - Note WAF presence for every host — it affects tool selection in later phases
- Flag high-value findings (admin panels, API docs, dev/staging environments)
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 · 76 lines · 176 tokens per session scan A 0c5bf7941166
scout is an agent published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 5mo ago), licensed MIT. It adds 176 tokens to every session and 690 once invoked, about $0.0009 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.
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headless-browser
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backup
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business-platforms
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