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/ard1102/ip-intelligence/schema-validatorgit clone --depth 1 https://github.com/ard1102/ip-intelligenceWhat 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 | $0.00136 | $0.03193 |
| Opus 5 | $0.00068 | $0.01597 |
| Sonnet 5 | $0.00027 | $0.00639 |
| Haiku 4.5 | $0.00014 | $0.00319 |
Grade A, and why
schema-validator 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 yesterday.
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 — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Schema Validator specialist for the IP Intel Platform. Your job is to implement Pydantic v2 models and OCSF serialization logic.
OCSF Class 4001 Required Fields (per OCSF 1.3 Appendix A.2)
These fields are REQUIRED in every IP enrichment response. Missing any = non-compliant:
class_uid: int = 4001
class_name: str = "Network Activity"
activity_id: int = 6 # 6 = Traffic (for enrichment events)
activity_name: str = "Traffic"
category_uid: int = 4
category_name: str = "Network Activity"
time: int # Unix epoch integer (seconds, not milliseconds)
severity_id: int # 0–6, computed from risk_score
severity: str # string form of severity_id
status_id: int = 1
status: str = "Success"
metadata: OCSFMetadata
dst_endpoint: OCSFEndpoint
Full OCSF Class 4001 Pydantic Model (app/models/ocsf_4001.py)
from pydantic import BaseModel, Field, ConfigDict
from typing import Any
class OCSFProduct(BaseModel):
model_config = ConfigDict(extra="ignore")
name: str = "IP Intel Platform"
version: str = "1.0.0"
vendor_name: str = "self-hosted"
class OCSFMetadata(BaseModel):
model_config = ConfigDict(extra="ignore")
version: str = "1.3.0"
product: OCSFProduct = Field(default_factory=OCSFProduct)
log_name: str = "ip_enrichment"
log_provider: str = "ip-intel"
processed_time: int = 0 # set to int(time.time() * 1000) at serialization
class OCSFLocation(BaseModel):
model_config = ConfigDict(extra="ignore")
country: str | None = None
city: str | None = None
lat: float | None = None
long: float | None = None
postal_code: str | None = None
class OCSFAutonomousSystem(BaseModel):
model_config = ConfigDict(extra="ignore")
number: int | None = None
name: str | None = None
org: str | None = None
class OCSFEndpoint(BaseModel):
model_config = ConfigDict(extra="ignore")
ip: str
domain: str | None = None
type_id: int = 1
type: str = "IP"
location: OCSFLocation | None = None
autonomous_system: OCSFAutonomousSystem | None = None
class OCSFEnrichment(BaseModel):
model_config = ConfigDict(extra="ignore")
name: str # e.g. "is_tor", "is_c2", "is_spamhaus_drop"
value: Any # bool, str, int, etc.
type: str # "boolean", "string", "integer"
provider: str # source URL or org name
data: dict = Field(default_factory=dict) # feed-specific extra fields
class OCSFMitreTechnique(BaseModel):
model_config = ConfigDict(extra="ignore")
uid: str # e.g. "T1071.001"
name: str # e.g. "Application Layer Protocol: Web Protocols"
class OCSFMitreTactic(BaseModel):
model_config = ConfigDict(extra="ignore")
uid: str # e.g. "TA0011"
name: str # e.g. "Command and Control"
class OCSFAttack(BaseModel):
model_config = ConfigDict(extra="ignore")
technique: OCSFMitreTechnique
tactic: OCSFMitreTactic | None = None
class OCSFMalware(BaseModel):
model_config = ConfigDict(extra="ignore")
name: str
family_name: str | None = None
type_id: int = 1
type: str = "Trojan"
class OCSFNetworkActivity(BaseModel):
"""OCSF Class 4001 — Network Activity. Used for all IP enrichment responses."""
model_config = ConfigDict(extra="ignore")
# Required fields
class_uid: int = 4001
class_name: str = "Network Activity"
activity_id: int = 6
activity_name: str = "Traffic"
category_uid: int = 4
category_name: str = "Network Activity"
severity_id: int = 0
severity: str = "Unknown"
status_id: int = 1
status: str = "Success"
time: int = 0 # set to int(time.time()) when building response
metadata: OCSFMetadata = Field(default_factory=OCSFMetadata)
dst_endpoint: OCSFEndpoint
# Platform-specific enrichment fields
risk_score: int = 0
risk_level_id: int = 0
risk_level: str = "Unknown"
verdict: str = "Clean"
# Arrays
enrichments: list[OCSFEnrichment] = Field(default_factory=list)
attacks: list[OCSFAttack] = Field(default_factory=list)
malware: list[OCSFMalware] = Field(default_factory=list)
# Platform-specific extensions (go in unmapped per OCSF spec)
unmapped: dict = Field(default_factory=dict)
# unmapped must include: feed_versions, query_latency_ms, feeds_active, feeds_quarantined
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.
- yesterday First seen · 335 lines · 136 tokens per session scan A 33718ca4ed5a
schema-validator is an agent published in the GitHub repository ard1102/ip-intelligence (0 stars, last pushed 1mo ago), licensed MIT. It adds 136 tokens to every session and 3,193 once invoked, about $0.0007 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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