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 HoangNguyen0403/agent-skills-standard --skill cyber-detection-validationgit clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standardWrote 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/hoangnguyen0403/agent-skills-standard/cyber-detection-validation)<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/cyber-detection-validation"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/cyber-detection-validation/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/hoangnguyen0403/agent-skills-standard/cyber-detection-validation"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/cyber-detection-validation.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 | $0.00054 | $0.00885 |
| Opus 5.5 | $0.00022 | $0.00354 |
| Sonnet 5.5 | $0.00011 | $0.00177 |
| Haiku 4.5 | $0.00005 | $0.00089 |
Grade A, and why
cyber-detection-validation 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cyber Detection Validation
Priority: P0 (CRITICAL)
No defensive outcome without linked action and observation evidence.
Input: control hypothesis, permitted action, scope/approval, mode (analysis, replay, isolated-lab-validation, defensive-verification), entity, window, expected observation, stop condition.
Process: classify active effects (active: true for any interaction outside supplied-artifact reasoning; reading supplied events/files is non-active analysis); verify fresh host gate before active actions; capture ActionReceipt and ObservationRecord; enforce transitive binding chain: ObservationRecord.action_receipt_ref -> ActionReceipt.gate_ref -> GateDecision.request_ref -> ActionRequest.
Output: purple outcome enum, finding status, evidence references, limitations, stage fidelity, owner.
Workflow
- Declare step mode and effects:
analysis,replay,isolated-lab-validation, ordefensive-verification. - Preflight host gate for active effects: evaluate ActionRequest and GateDecision immediately before dispatch.
- Execute bounded action; bind ActionReceipt to correlation key
(run_id, attempt_id, test_id). - Capture ObservationRecord within defined time window; enforce unique
observation_idand transitive binding chain. - Classify purple defensive outcome:
blocked,prevented,detected,responded, ortelemetry-gap. - Report stage fidelity: replay reports only exercised stages (e.g., parsing/correlation); lab reports observed sensor/control stages.
- Run teardown plan; record CleanupResult (
verified-clean,residual,unverified,not-applicable).
Rules
- Active operations require fresh host capability proofs; reading supplied synthetic events without host mutation is non-active analysis. Mode never overrides active effects classification.
- Controlled synthetic fixtures only. No real credentials, malware, production targets, or data exfiltration.
- Mandatory transitive binding: ObservationRecord must uniquely resolve through ActionReceipt to GateDecision. Cross-run, cross-fixture, or conflicting keys are rejected.
- Replay stage fidelity: Replay of supplied synthetic events reports only exercised processing stages (e.g., ingestion, correlation), never sensor acquisition or prevention unless independently evidenced (AC-CLV-02).
- Telemetry gap: An exercised action without usable matching observation is
telemetry-gap(AC-CLV-12). An observation alone cannot prove an action occurred. - Purple enum definitions:
blocked: denied or could not run;prevented: control stopped action;detected: observation identified behavior;responded: independently evidenced approved response;telemetry-gap: action exists without observation. - Teardown disclosure: Incomplete or unverified cleanup reports
residualorunverifiedwith accountable owner (AC-CLV-13). - Carry shared evidence fields from cyber-evidence and use lab execution gate when validating in labs.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed · +15 lines 5cafcc7db51b
- 28d ago First seen · 40 lines · 54 tokens per session scan A 2dfbc87aec1e
cyber-detection-validation is a skill published in the GitHub repository HoangNguyen0403/agent-skills-standard (582 stars, last pushed today), licensed MIT. It adds 54 tokens to every session and 885 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-30.
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