business-operations-skills

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SKILL.md (first lines)

# Business Operations — Domain Orchestrator

The BizOps surface is **internal**: how the company actually runs. This orchestrator forks its conversation context, routes your inquiry to one of six sub-skills, then returns a tight digest to the parent thread. The heavy ingestion (vendor catalogs, process interviews, multi-doc SOP intake) stays in the forked context.

## When to invoke

| Symptom | Sub-skill to route to |
|---|---|
| "Where does the work spend most of its time waiting?" | `process-mapper` |
| "Is this vendor delivering against the SLA?" | `vendor-management` |
| "Do we have enough people to ship in Q3?" | `capacity-planner` |
| "I need to brief the company on a re-org" | `internal-comms` |
| "Write me a runbook for the incident response process" | `knowledge-ops` |
| "Why is our software spend up 40% YoY?" | `procurement-optimizer` |

## Routing logic (deterministic)

The orchestrator classifies the inquiry by **signals** detected in the prompt. Two-signal threshold for confident routing; one-signal triggers a clarifying question.

### Signal table

| Signal class | Keywords | Sub-skill |
|---|---|---|
| **PROCESS** | bottleneck, cycle time, waiting, handoff, BPMN, process map, workflow | `process-mapper` |
| **VENDOR** | vendor, supplier, SLA, contract, third-party, MSA, SaaS subscription, renewal | `vendor-management` |
| **CAPACITY** | headcount, capacity, utilization, planning, hiring sequence, FTE | `capacity-planner` |
| **COMMS** | all-hands, internal newsletter, announcement, change management, FAQ, town hall | `internal-comms` |
| **KNOWLEDGE** | SOP, runbook, knowledge base, wiki, playbook, documentation, onboarding doc | `knowledge-ops` |
| **PROCUREMENT** | spend, procurement, purchase, supplier rationalization, software audit, SaaS sprawl | `procurement-optimizer` |

If signals are mixed (e.g., "vendor SLA + spend audit"), run the **highest-confidence sub-skill first**, then chain into the second one in a follow-up forked turn.

### Fallback

If no signal class scores ≥ 2, ask **one** clarifying question naming the two most likely candidates. Do NOT guess silently.

## Workflow (Matt Pocock grill discipline)

Derived from Matt Pocock's `grill-with-docs` pattern: **explore-then-ask, one question per turn with a recommended answer, walk the decision tree depth-first, track dependencies, anchor every challenge in the documented canon** (`references/`).

### Step 1 — Explore before asking

Before any clarifying question, check:
- Does the user's working directory already contain a process map, vendor catalog, SOP, or org chart we can grep?
- Does the inquiry already disambiguate the lane (e.g., "vendor SLA review" — that's `vendor-management`, no question needed)?
- Is the lane unambiguous from filenames mentioned (`procurement-Q3.csv` → procurement)?

If the codebase resolves the lane, **route silently**. Don't ask.

### Step 2 — If still ambiguous, ONE forcing question with a recommended answer

Matt's rule: never bundle questions. Never default to "what do you think?". Always offer your recommendation.

Pattern:
```
Q1/1: [precise question naming the two candidate lanes]
Recommended: [Lane X, because <one-sentence rationale from the signal table>]

(Confirm, or override?)
```

Wait for the user's response. **Then** route. Never guess silently after a turn that asked a question.

### Step 3 — Forking decision-tree walk (only if the inquiry crosses lanes)

If the user's inquiry legitimately crosses two lanes (e.g., "vendor SLA + spend audit" = VENDOR + PROCUREMENT), walk the tree **depth-first**:

1. Resolve the higher-confidence lane first → run that sub-skill in forked context → return digest
2. Ask: "Should we now run [second lane]? My recommendation: yes, because [dependency reason]."
3. Only after explicit user confirmation, run the second sub-skill

Do NOT chain silently. Each fork is an explicit user-confirmed step.

### Step 4 — Invoke sub-skill in forked context

Each sub-skill is invoked with the original prompt + a digest of any structured inputs (file paths, JSON inputs). The fork keeps heavy ingestion (vendor catalog, process transcripts, SOP source documents) out of the parent context.

### Step 5 — Return digest with cited canon challenge

When the sub-skill completes, return a **≤ 200-word digest** to the parent thread:

- What was analyzed
- Top 3 findings (each anchored in a reference doc citation — e.g., "Goldratt's Theory of Constraints: optimize the bottleneck, not the non-constraint")
- Top 3 next actions (named owners if possible)
- Path to the artifact(s) produced
- **One grill challenge** for the user, cited: "Your value-add ratio is 12%. Lean canon (Womack & Jones 1996) classifies <15% as waste-heavy. What's blocking process redesign — political, technical, or budget?"

The parent agent can then ask follow-ups (each triggering new forked invocations).

## Forcing-question library (grill-with-docs pattern)

When the user has provided enough context to enter a lane, the orchestrator may grill them on the **decisions inside that lane** before invoking the sub-skill. One question per turn, each with a recommended answer + canon citation. Examples:

- **PROCESS lane**: "Before mapping: do you have measured cycle times per stage, or only estimates? Recommended: insist on measured data for the top-3 longest stages. Anti-pattern (Goldratt 1984): map estimates, optimize the wrong constraint."
- **VENDOR lane**: "Before scoring: what's your tier-1 criticality threshold — by spend ($X/year), or by operational dependency (revenue-blocking if vendor fails)? Recommended: operational dependency. Anti-pattern (Gartner TPRM): spend-only tiering misses critical low-spend vendors like the HVAC vendor in the Target breach."
- **CAPACITY lane**: "Before modeling: are you planning for utilization or throughput? Recommended: throughput (Little's Law). Anti-pattern (DORA): planning for utilization > 80% destroys throughput via queueing."

Never run a sub-skill until the lane-defining decision is locked.

## Assumptions

1. The user is acting on behalf of an organization with ≥ 10 employees (smaller orgs don't need this surface).
2. The user has access to the data the sub-skill needs (process docs, vendor list, spend export, etc.) — or accepts the skill's templated dummy data.
3. The user wants **deterministic, repeatable analysis** over LLM-flavored prose. Every sub-skill ships stdlib-only Python tools.

## Non-goals

- Not a substitute for an ERP, vendor management platform (Vendr, Tropic), or capacity-planning SaaS (Float, Runn).
- Does not store state across sessions — every invocation is self-contained.
- Does not call external APIs from Python tools (stdlib only, by design).

## Distinct from

- **`business-growth/*`** — that's the **external sales motion** (CSM, sales engineering, RevOps). BizOps is **internal**.
- **`c-level-advisor/coo-advisor`** — that's strategic COO judgment ("should we restructure?"). BizOps is tactical ("here's the process map with bottlenecks").
- **`engineering/slo-architect`** — that's system reliability with SLO/SLI/error budgets. `process-mapper` is **business process** reliability, not system reliability.
- **`engineering/llm-wiki`** — that's a **personal** PKM (Karpathy's pattern). `knowledge-ops` is **company-wide** SOP authoring.

## Output artifacts

From bughunt8/skills, MIT.

More from bughunt8/skills