Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ChipAlexandru/strategy-consultantnpx agentmods add commands/chipalexandru/strategy-consultant/engagementWrote 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/commands/chipalexandru/strategy-consultant/engagement)<a href="https://agentmods.dev/commands/chipalexandru/strategy-consultant/engagement"><img src="https://agentmods.dev/badge/commands/chipalexandru/strategy-consultant/engagement/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/commands/chipalexandru/strategy-consultant/engagement"><img src="https://agentmods.dev/badge/commands/chipalexandru/strategy-consultant/engagement.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 | $0.00022 | $0.01110 |
| Opus 5 | $0.00011 | $0.00555 |
| Sonnet 5 | $0.00004 | $0.00222 |
| Haiku 4.5 | $0.00002 | $0.00111 |
Grade A, and why
engagement 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/engagement — Full Consulting Engagement
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Important: This plugin is designed to handle 80–90% of the analytical workload in a strategy engagement — research, evidence validation, structured synthesis, and report drafting — so that the consultant can focus on the 10–20% that creates unique value: client relationship judgment, proprietary insight, and final recommendations. All outputs are intended as high-quality working drafts for expert review, not finished deliverables.
Run a complete consulting-grade analytical engagement on a business question, producing an executive-grade client report.
Usage
/engagement <business question or topic>
Arguments
business question or topic— The business problem, client brief, or analytical question to investigate. Can be:- A direct question: "Should we enter the European EV charging market?"
- A vague brief: "The client wants to grow in Asia"
- A file upload: client brief, RFP, or project description
If no topic is provided, prompt the user to supply one.
Workflow
This command invokes the engagement-manager skill, which orchestrates the full end-to-end workflow. The phase numbering below mirrors the orchestrator; see skills/engagement-manager/SKILL.md for the authoritative phase logic, gates, and state-file conventions.
Phase 1 — Problem Definition
Invoke the problem-definition skill to sharpen the business question into a decision-oriented problem statement with a Precision Anchor, Client Question Checklist, and Deliverable Blueprint. Checkpoint 1: user confirms before proceeding.
Phase 2 — Hypothesis Tree (Optional)
Invoke hypothesis-tree only when structured decomposition adds value. Skip when the question is narrow enough for direct research.
Phase 2.5 — Data Source Inquiry (Mandatory)
Ask the user three required questions about available data — internal/client data, external expert interviews, and other reference material. The answers determine the research scenario (A/B/C/D/E) and are recorded in step0-answers.md.
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.
- 9d ago First seen · 74 lines · 22 tokens per session scan A 7f60bbdbf965
engagement is a command published in the GitHub repository ChipAlexandru/strategy-consultant (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 22 tokens to every session and 1,110 once invoked, about $0.0001 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.