coo-advisor

Overview of coo-advisor skill

What coo-advisor is built to do

coo-advisor is a Claude skill for internal operations leadership: turning strategy into execution systems, designing operating cadence, improving processes, cascading OKRs, and diagnosing bottlenecks as a company scales. It is best suited for founders, COOs, Chiefs of Staff, RevOps/Ops leaders, and team leads who need practical operating structure rather than generic management advice.

Best fit for Internal Operations teams

The strongest use case is coo-advisor for Internal Operations in scaling startups or growing teams where execution is becoming harder to coordinate. Use it when you need to answer questions like: “Which process is constraining growth?”, “How should we run weekly/monthly business reviews?”, “Are our OKRs aligned?”, or “What breaks between Seed and Series B?”

What makes this skill more useful than a generic COO prompt

The coo-advisor skill includes structured references for operational cadence, process frameworks, and scaling-stage playbooks, plus Python tools for OKR tracking and operational efficiency analysis. That gives the agent reusable operating models instead of relying only on broad business reasoning. The emphasis is practical: meeting rhythm, async defaults, Theory of Constraints, maturity scoring, OKR health, and stage-specific scaling tradeoffs.

When this skill may not be the right fit

Do not treat coo-advisor as a legal, HR compliance, finance, or enterprise transformation authority. It can help structure operating decisions, but it needs your company context and current metrics. It is less useful for very early teams that have not found product-market fit and may be harmed by premature process.

How to Use coo-advisor skill

coo-advisor install and files to read first

Install with:

npx skills add alirezarezvani/claude-skills --skill coo-advisor

After installing, start with SKILL.md for scope and trigger language. Then read these files in order:

1. references/scaling_playbook.md — stage-specific failure modes and operating choices.
2. references/ops_cadence.md — meeting cadence, async updates, decision rhythm, reporting.
3. references/process_frameworks.md — Theory of Constraints, process mapping, Lean-style improvement.
4. scripts/okr_tracker.py — OKR scoring and alignment report logic.
5. scripts/ops_efficiency_analyzer.py — process maturity and bottleneck analysis.

This reading path matters because the skill is not just a prompt style; it pairs advisory language with operational frameworks and optional scripts.

Inputs the skill needs for high-quality advice

For strong coo-advisor usage, give the agent operational facts, not just a goal. Include company stage, headcount, revenue range if relevant, team structure, current cadence, key bottleneck symptoms, existing OKRs, process ownership, and constraints.

Weak prompt: “Help us improve operations.”

Stronger prompt: “Use coo-advisor to assess our Series A SaaS operations. We are 45 people, $4M ARR, sales cycle is slowing, engineering says roadmap churn is the bottleneck, leadership meets weekly for 90 minutes, teams use quarterly OKRs but KRs are mostly activity-based. Recommend the highest-leverage operating changes for the next 30 days.”

The stronger version helps the skill choose between cadence redesign, OKR cleanup, bottleneck analysis, and scaling-stage guidance.

Practical workflow for operations decisions

A useful workflow is:

1. Ask coo-advisor to classify your current scaling stage and likely operating failure modes.
2. Map the value stream or execution system you care about, such as lead-to-cash, roadmap-to-release, or hire-to-productivity.
3. Use the skill to identify the likely constraint and separate symptoms from root causes.
4. Redesign only the necessary cadence: async updates, decision meetings, reviews, escalation paths.
5. Convert recommendations into 30-day operating experiments with owners and success metrics.

If you use the scripts, run python scripts/ops_efficiency_analyzer.py with sample data first, then adapt the input JSON format. For OKRs, run python scripts/okr_tracker.py --input okrs.json --output report.txt once your objectives and KRs are structured.

Prompt patterns that trigger the right mode

Use direct intent language such as “act as COO advisor,” “analyze our operating cadence,” “find the bottleneck,” “cascade these OKRs,” “design a scaling operating model,” or “review this process for maturity.” Paste relevant current-state material: meeting calendar, OKR table, process steps, metrics, decision logs, or leadership concerns. Ask for tradeoffs and sequencing, not just a polished plan.

coo-advisor skill FAQ

Is coo-advisor only for people with a COO title?

No. The coo-advisor skill is useful for anyone responsible for execution systems: founders, Chiefs of Staff, department heads, operations managers, RevOps leaders, and program leads. The key requirement is ownership of cross-functional execution, not a specific title.

How is it different from asking Claude for operations advice?

A generic prompt may produce reasonable best practices. coo-advisor brings a narrower operating lens: OKR cascades, meeting cadence, process maturity, bottleneck diagnosis, and scaling-stage patterns. It is more likely to ask for throughput, ownership, decision rights, and company stage because those factors change the right recommendation.

Can beginners use coo-advisor?

Yes, but beginners should start with a narrow problem. Instead of asking for a full operating model, ask for one artifact: a weekly business review agenda, a first OKR cascade, a bottleneck map, or a 30-day process improvement plan. The references are practical enough to learn from, but the quality improves when you provide real context.

When should I avoid using it?

Avoid using coo-advisor to justify process for its own sake. If your company is pre-PMF, under 10 people, or still changing direction weekly, heavy OKRs and meeting systems may slow learning. Also avoid using it as a substitute for direct employee conversations, customer evidence, or executive judgment.

How to Improve coo-advisor skill

Improve coo-advisor results with better operating context

The fastest way to improve coo-advisor output is to describe the operating system as it exists today. Include current meetings, who attends, decisions made, recurring blockers, cycle times, ownership gaps, and what has already been tried. If possible, provide before/after metrics such as lead response time, release frequency, hiring cycle time, implementation backlog, or customer handoff defects.

Common failure modes to watch for

The skill can over-structure a vague problem if you do not state company stage and tolerance for process. It may also propose cadence changes when the real constraint is role clarity, tooling, decision rights, or capacity. Ask it explicitly to distinguish “symptom,” “constraint,” “recommended experiment,” and “metric to validate.”

Iterate from diagnosis to operating experiments

After the first answer, do not ask only for more detail. Ask for a decision-ready version: “Rank these recommendations by leverage and implementation cost,” “Turn this into a two-week experiment,” “What should we stop doing?”, or “Which meeting can be replaced by async reporting?” This pushes the skill toward operational tradeoffs.

Customize the skill for your company

If you maintain a local version, add your company’s operating principles, standard OKR format, meeting templates, planning calendar, and process metrics. You can also extend the JSON examples used by okr_tracker.py and ops_efficiency_analyzer.py so the tools reflect your real departments, KPIs, and maturity criteria. This makes coo-advisor more specific without turning it into generic corporate policy text.