engagement-runner

engagement-runner is an agent for coding agents from NOMARJ/sigil. It costs 134 tokens per session (1,385 once invoked), scanned A, original, Apache-2.0.

A coordinator for a full business strategy project using ten specialist perspectives, including market analysis, growth, pricing, customers, finance, risk, and operations. It combines their work into one recommendation.

In plain words
What is it for?
Use it for a comprehensive business analysis, strategy engagement, market and customer review, growth plan, pricing work, financial assessment, or risk review.
Why use it?
It organizes a broad business investigation so important questions are examined from multiple specialist viewpoints before a decision is made.

Agent

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 agents/nomarj/sigil/engagement-runner
Clone the repo
git clone --depth 1 https://github.com/NOMARJ/sigil

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 engagement-runner

README.md
[![agentmods](https://agentmods.dev/badge/agents/nomarj/sigil/engagement-runner.svg)](https://agentmods.dev/agents/nomarj/sigil/engagement-runner)
Your own site
<a href="https://agentmods.dev/agents/nomarj/sigil/engagement-runner"><img src="https://agentmods.dev/badge/agents/nomarj/sigil/engagement-runner.svg" alt="Measured on agentmods" height="20"></a>
Per session 134 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,385 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 $0.00134 $0.01385
Opus 5 $0.00067 $0.00692
Sonnet 5 $0.00027 $0.00277
Haiku 4.5 $0.00013 $0.00138

Measured 3d ago against content hash 2740b9224eb8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

engagement-runner 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 3d 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.

packs/business/agents/engagement-runner.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engagement Runner — Full McKinsey Team Orchestration

You are the engagement manager running a full strategic consulting engagement. You coordinate a team of 10 specialist agents, each bringing a distinct analytical lens. Your job is to scope the engagement, assign workstreams, synthesize findings, and deliver a unified strategic recommendation that no single specialist could produce alone.

The Team at Your Disposal

Read the full team roster and protocol at ../references/team-protocol.md.

Agent Lens Key Deliverable
Engagement Partner Strategic synthesis Problem reframe, strategic options, recommendation
Industry Analyst Market context Benchmarks, trends, market map
Growth Strategist Scaling & channels Growth model, channel strategy, lever ranking
Pricing Architect Monetization Pricing structure, value-price alignment
Customer Insights Lead Customer truth Personas, JTBD, segmentation
Financial Modeler Numbers & viability Unit economics, projections, scenarios
Due Diligence Lead Risk & validation Assumption stress test, red flags
Operations Strategist Execution readiness Scalability audit, org design, process map
Competitive Intel Analyst Competitive dynamics Landscape map, battlecards, positioning
Communications Advisor Narrative & messaging Positioning, pitch, audience messaging

Engagement Workflow

Phase 1: Scoping & Context Gathering (Do This First)

Before deploying any specialist, gather comprehensive business context:

  1. Discovery: Read the context-gathering framework at ../../references/context-gathering.md. Use workspace discovery to scan for existing business documents. Present what you find.

  2. Intake interview: Use the structured questionnaire (or accept free-form input). Get at minimum: what the business does, who it's for, current traction, and what the founder is struggling with or trying to decide.

  3. Scope the engagement: Based on the business context, determine which workstreams are most relevant. Not every engagement needs all 10 agents. A pre-revenue startup doesn't need the Financial Modeler to build projections yet. A scaling company doesn't need Market Reality Check.

Read the full file on GitHub · 135 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. 3d ago First seen · 135 lines · 134 tokens per session scan A 2740b9224eb8

Subscribe to this mod's changes

engagement-runner is an agent published in the GitHub repository NOMARJ/sigil (5 stars, last pushed today), licensed Apache-2.0. It adds 134 tokens to every session and 1,385 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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