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 skills add Roshu18/bearstrike-ai --skill recongit clone --depth 1 https://github.com/Roshu18/bearstrike-aiWrote 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/skills/roshu18/bearstrike-ai/recon)<a href="https://agentmods.dev/skills/roshu18/bearstrike-ai/recon"><img src="https://agentmods.dev/badge/skills/roshu18/bearstrike-ai/recon/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/skills/roshu18/bearstrike-ai/recon"><img src="https://agentmods.dev/badge/skills/roshu18/bearstrike-ai/recon.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 | $0.00017 | $0.00313 |
| Opus 5 | $0.00009 | $0.00156 |
| Sonnet 5 | $0.00003 | $0.00063 |
| Haiku 4.5 | $0.00002 | $0.00031 |
Grade A, and why
recon 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 9d 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
recon
Workflow
- Subdomain discovery
- subfinder -d
- amass enum -d
- DNS mapping
- dnsenum
- theHarvester -d -b all
- Service discovery
- nmap -sV -Pn
- Web fingerprinting
- httpx
- whatweb
- wafw00f
- Content discovery
- ffuf/gobuster/dirsearch
- katana for URL crawl
Exit criteria
- Live hosts list, open ports, tech stack, WAF status, and high-value endpoints recorded.
High-yield endpoint map strategy
Collect endpoints from three sources and merge:
- Live probing and crawl (httpx/katana)
- Historical archives (gau/waybackurls)
- Parameter discovery (arjun)
Tag endpoints quickly by risk:
- auth-critical: login, reset, token, oauth, session
- object-critical: /user/, /account/, /invoice/, /order/, /api/v*/id
- admin/internal: /admin, /internal, /debug, /graphql
Recon stop condition
Stop broad discovery when either condition is true:
- 20+ high-value unique endpoints are mapped, or
- Two consecutive recon runs produce only duplicates.
Then switch to verification-focused testing.
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.
- 9d ago First seen · 53 lines · 17 tokens per session scan A 046188d40500
recon is a skill published in the GitHub repository Roshu18/bearstrike-ai (4 stars, last pushed 5mo ago), licensed MIT. It adds 17 tokens to every session and 313 once invoked, about $0.0001 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 2026-08-31.
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