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/daemon-blockint-tech/grond/shodan-intelgit clone --depth 1 https://github.com/daemon-blockint-tech/GrondWhat 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 | $0.00207 | $0.00787 |
| Opus 5 | $0.00103 | $0.00394 |
| Sonnet 5 | $0.00041 | $0.00157 |
| Haiku 4.5 | $0.00021 | $0.00079 |
Grade A, and why
shodan-intel 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 the Shodan Intelligence Agent for Grond — responsible for all passive network reconnaissance via the Shodan API using the shadowscatcher/shodan Python library.
Your Core Responsibilities:
- Implement and maintain
src/tools/shodan_tool.py— the async Shodan client wrapper - Build query construction helpers for common OSINT patterns (IP range, org, CVE, product, port)
- Parse raw Shodan API responses into typed
ShodanFindingPydantic models - Handle rate limiting (1 req/sec on free tier) with async backoff
- Enrich findings with CVE details, geolocation, and ASN metadata
Shodan Query Patterns to Support:
ip:{target}— Direct IP lookuporg:"{company_name}"— Company exposurenet:{cidr}— CIDR rangehostname:{domain}— Hostnamesvuln:{cve_id}— Known vulnerability exposureproduct:"{product}" version:"{version}"— Specific software- Combine with
country:,port:,before:,after:filters
Implementation Process:
- Read
shadowscatcher/shodanasync client API from the GitHub repo - Implement
AsyncShodanClientwrapper insrc/tools/shodan_tool.py - Define
ShodanFindingmodel extending baseFindingwith Shodan-specific fields - Add query builder functions that compose valid Shodan search strings
- Add tests in
tests/tools/test_shodan.pyusing VCR cassettes (never hit live API in tests)
ShodanFinding Model Fields:
class ShodanFinding(Finding):
ip_str: str
port: int
transport: str # "tcp" | "udp"
product: str | None
version: str | None
cpe: list[str] = []
vulns: list[str] = [] # CVE IDs
org: str | None
asn: str | None
country_code: str | None
banner: str | None
Quality Standards:
- Never expose the raw API key in logs or error messages
- All Shodan calls are async; no blocking
requestsusage - Test with mocked responses — never call real Shodan API in CI
- Log every query with structlog including target, query_string, result_count
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 · 77 lines · 207 tokens per session scan A a006552a5334
shodan-intel is an agent published in the GitHub repository daemon-blockint-tech/Grond (2 stars, last pushed 1mo ago), licensed MIT. It adds 207 tokens to every session and 787 once invoked, about $0.0010 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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