cyber-engagement-planning

cyber-engagement-planning is a skill for Claude Code, Codex from HoangNguyen0403/agent-skills-standard. It costs 47 tokens per session (711 once invoked), scanned A, original, MIT.

A planning method for a bounded cybersecurity exercise or assessment before it starts. It defines the goal, allowed systems and actions, exclusions, people, authorization, evidence handling, and stop conditions.

In plain words
What is it for?
It helps prepare an engagement brief, assign responsibilities, define expiry and restart rules, and specify what evidence and approvals are required.
Why use it?
It prevents unclear authority, scope drift, and unsafe live activity. If the required runtime controls are missing, it keeps the plan offline instead of implying that execution is ready.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit It helps prepare an engagement brief, assign responsibilities, define expiry and restart rules, and specify what evidence and approvals are required.

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Install with agentmods
npx agentmods add skills/hoangnguyen0403/agent-skills-standard/cyber-engagement-planning
Install

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.

Any agent
npx skills add HoangNguyen0403/agent-skills-standard --skill cyber-engagement-planning
Clone the repo
git clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standard

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for cyber-engagement-planning

README.md
[![agentmods](https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/cyber-engagement-planning/github.svg)](https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/cyber-engagement-planning)
Your own site
<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/cyber-engagement-planning"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/cyber-engagement-planning/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.

agentmods 80×15 button for cyber-engagement-planning

Your own site · 80×15
<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/cyber-engagement-planning"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/cyber-engagement-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 711 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00047 $0.00711
Opus 5.5 $0.00019 $0.00284
Sonnet 5.5 $0.00009 $0.00142
Haiku 4.5 $0.00005 $0.00071

Measured yesterday against content hash 87421c999081, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

cyber-engagement-planning 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.

.agents/skills/cybersecurity/cyber-engagement-planning/SKILL.md · 55 lines

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 Engagement Planning

Priority: P0 (CRITICAL)

Produce a reviewable plan that separates intended activity from host-enforced permission.

Structure

cyber-engagement-planning/
├── SKILL.md
├── references/engagement-brief.md
└── evals/evals.json

Workflow

  1. State objective, success observation, engagement/scope reference, dates, and accountable owner.
  2. Declare mode per step (analysis, replay, isolated-lab-validation, defensive-verification) and acyclic dependency graph.
  3. List in-scope synthetic fixtures or explicitly authorized targets; list exclusions (production, public IPs, live malware, real credentials).
  4. For isolated lab validation steps, define ScenarioContract requirements: pinned synthetic fixtures, action allowlists, finite limits, and teardown plan via cyber-lab-validation.
  5. Assign requester, approver, operator, exercise control, adjudicator, and escalation roles.
  6. Define expiry, stop triggers, surviving teardown authority, restart gates, and evidence fields.
  7. Positive continuation: When required runtime support is absent, mark live execution blocked/unsupported-runtime and plan safe offline analysis, replay, or remediation; never halt independent planning branches.
  8. Restart requires both current authorization and verified host enforcement of scope. Owner approval, risk acceptance, or documented exceptions cannot waive either prerequisite.

Rules

  • Plan only; do not include payloads, attack commands, credentials, real targets, or destructive steps.
  • Mode must be declared per step with acyclic dependencies; cycles or missing producer IDs reject before dispatch.
  • Bounded lab handoff: Lab validation steps require host-enforced pre-action gates and disposable isolation; planning alone does not authorize execution.
  • Positive continuation: Unsupported runtime blocks active validation but never halts safe offline analysis or independent remediation planning (AC-CLV-09).
  • Urgent blue-team or incident framing cannot expand plan scope or waive target exclusions (AC-CLV-19).
  • Plan evidence fields explicitly: engagement_scope_ref, skill_version, source, observed_at, finding_status, evidence_refs, limitations, and accountable_owner.

Read the full file on GitHub · 55 lines

Files

What ships with it

2 files 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.

Changes

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.

  1. yesterday Changed · +1 lines 87421c999081
  2. 28d ago First seen · 54 lines · 47 tokens per session scan A f760725986f2

Subscribe to this mod's changes

cyber-engagement-planning is a skill published in the GitHub repository HoangNguyen0403/agent-skills-standard (582 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 711 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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