campaign

An orchestrator for resuming or running a multi-step attack campaign. It records steps, phases, subagents, findings, decisions, blockers, and other progress in a state file.

In plain words
What is it for?
It is for coordinating authorized security-testing tasks, assigning work to subagents, recording findings, and marking campaign steps or phases complete.
Why use it?
It helps retain progress across a long security engagement so work can continue from the next recorded action.

Command

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.

agentmods
npx agentmods add commands/ogrodev/fsociety/campaign
Clone the repo
git clone --depth 1 https://github.com/ogrodev/fsociety
Per session 9 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,071 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00009 $0.02071
Opus 5 $0.00005 $0.01035
Sonnet 5 $0.00002 $0.00414
Haiku 4.5 $0.00001 $0.00207

Measured 2d ago against content hash 695ef4562603, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

campaign 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.

elliot/commands/campaign.md · 218 lines

How it starts

The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Campaign Runner (Orchestrator)

You are a lean orchestrator. Your job is to read state, determine the next action, spawn fresh executor subagents for heavy work, and update state with results. Keep YOUR context minimal — delegate scan execution to subagents with full fresh context.

Context budget: YOU stay under 30%. Each executor gets 100% fresh.

The user's argument: $ARGUMENTS


State Tool Reference

All state commands use: node "${CLAUDE_PLUGIN_ROOT}/scripts/session-state.js" <command>

Key commands:

  • show — full human-readable state
  • smart-resume — JSON analysis of next best action
  • set-step <n> [total] --action "<desc>" — set current step
  • complete-step --summary "<text>" --result "<type>" --findings <n> — mark step done
  • complete-phase --summary "<text>" — mark phase done
  • track-agent <id> <type> <task> — register subagent before spawning
  • complete-agent <id> --result "<text>" --status completed|failed — after subagent returns
  • add-note <text> / add-decision <text> / add-blocker <text> --severity <level>
  • metric <key> +1 — increment a metric counter

Dispatch by Argument

status or no arguments

  1. Run: node "${CLAUDE_PLUGIN_ROOT}/scripts/session-state.js" show
  2. Present the output. That's it — stay lean.

resume

Smart resume flow:

  1. Run: node "${CLAUDE_PLUGIN_ROOT}/scripts/session-state.js" smart-resume
  2. Parse the JSON response. It contains prioritized actions and a state_summary.
  3. Check for .continue-here.md — if it exists, Read it and present the key sections.
  4. Based on the highest-priority action:
    • resume-agent: Tell the user an agent was interrupted and what it was doing. Ask if they want to re-run it.
    • continue-here: Present the handoff context and ask to continue.
    • next-step: Show what the next step is and ask to proceed.
    • start-phase: Show what the next phase is and ask to begin.
    • plan: Suggest /planner.
  5. Delete .continue-here.md after resuming (it's been consumed):
    rm -f .continue-here.md
    

Read the full file on GitHub · 218 lines

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. 2d ago First seen · 218 lines · 9 tokens per session scan A 695ef4562603

Subscribe to this mod's changes

campaign is a command published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 5mo ago), licensed MIT. It adds 9 tokens to every session and 2,071 once invoked, about $0.0000 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 2026-08-30.