IntermediateAgent Skill

Business Operations Skills

Choose the right business operations workflow for a process, vendor, capacity, procurement or knowledge problem. Give your assistant a bounded question, relevant exports and the decision owner; this Skill routes the request to the appropriate specialist in the operations collection and brings the findings back into a concise brief for the team.

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01

What this Skill does

This Skill is the entry point for a collection of business-operations specialists. It distinguishes process, vendor, capacity, communications, knowledge and procurement work before choosing a lane, which is useful when a broad request contains several different operational problems.

Install the complete collection needed for the work: the router has no analysis scripts of its own. It coordinates the specialist results and prepares a decision brief, but does not function as an ERP or approve changes to suppliers, staffing or internal procedures.

02

What makes it different

01

Approach and advantage

Six specialist lanes separate operational questions with different data and methods. The routing step makes the selected approach visible, helping the team check that a staffing question is not being answered as a process-mapping or procurement problem.

02

What you can use it for

The final brief keeps the decision owner and bounded question in view while bringing specialist findings together. Supply the necessary exports and installed sibling Skills so the handoff can progress beyond a recommendation about which tool to use.

03

Before you install

Inputs to prepare

A bounded operations question, relevant exports, a decision owner, and the complete business-operations Skill collection.

Agent and runtime

Use a compatible agent that can discover the installed Skill and read its supporting files. Any external service or creative runtime must be configured separately.

Scope to confirm

The router has no analysis scripts of its own; sibling Skills supply them. It is not an ERP and does not approve process or vendor changes.

04

Install and get started

Copy this request into Codex or Claude Code. The assistant downloads the original repository at the specified commit, installs the complete files and checks required dependencies.

  1. Open Codex or Claude Code with local file and terminal access.
  2. Copy the request below into the app you are using. The assistant will select that app’s installation directory.
  3. Check the returned path and file checks. Start a new session if needed, then ask the assistant to use the installed Skill.
Install business-operations-skills in the app I am using and carry out the file installation, not just explain it. Original repository: https://github.com/alirezarezvani/claude-skills.git Commit: 6d2f02ea077eead1bee5411a31bcc6db5a11a70c Skill folder: business-operations/skills/business-operations-skills 1. Download this exact source into a new directory. Read SKILL.md and its setup references before running any bundled scripts. Do not substitute another author’s package. 2. For Codex, use ~/.agents/skills/business-operations-skills; for Claude Code, use ~/.claude/skills/business-operations-skills. Install only for my current app. This router requires the sibling Skills in business-operations/skills; install every direct child folder containing SKILL.md, and retain the repository checkout for repository-relative references. Separately distributed plugins are not automatically installed. Check all destination folders first; if any already exist, report differences before replacing them. 3. Compare the source and installed file lists and hashes. Inspect documented runtimes, dependencies and required connections. Configure only the local dependencies needed for this Skill; use an isolated environment when appropriate. Ask me to complete any account login locally, without putting credentials in chat. 4. Report the source commit, actual installation path, file-check results and any remaining runtime setup. Explain how to invoke business-operations-skills in this app. Check discovery separately from file copying; start a new session if needed. Do not run production tasks or claim a successful business outcome from installation alone.
05

Original Skill.md

This is the unchanged source SKILL.md for the reviewed version. Install the complete package to retain referenced scripts, assets, and instructions. Starter prompts below are EcomAgentTools examples.

---
name: business-operations-skills
description: Use when running, diagnosing, or designing internal business operations — process documentation, vendor SLAs, capacity planning, internal comms, SOP/runbook authoring, procurement spend. Triggers on "BizOps review", "where's the bottleneck", "vendor health", "internal SOP", "all-hands deck", "spend categorization", "capacity for Q3", "process mapping". Forks context to route to one of six BizOps sub-skills (process-mapper, vendor-management, capacity-planner, internal-comms, knowledge-ops, procurement-optimizer) and returns a digest. Distinct from business-growth (external sales motion) and c-level-advisor (strategic, not operational).
context: fork
license: MIT
metadata:
  version: 2.8.0
  author: claude-code-skills
  tags: [bizops, operations, process, vendor, capacity, sop, procurement, coo, orchestrator]
  compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]
---

# 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

Every sub-skill produces at least one artifact (markdown, CSV, or JSON) saved to the user's working directory. The orchestrator surfaces the file path in the digest.

## Anti-patterns (do not)

- ❌ Run all 6 sub-skills "to be thorough" — pick one based on signal, return digest, let user chain
- ❌ Auto-approve a vendor or process change — surface findings; the human decides
- ❌ Edit production process docs without asking — write to a new file, propose the diff
- ❌ Skip the digest step — parent context needs ≤ 200-word digest, not the full sub-skill output

## References

- See `c-level-advisor/coo-advisor` for strategic COO framing
- Path-B build pattern: `documentation/implementation/bizops-commercial-expansion-plan.md`
06

Get started

Starter prompts for the main use cases—copy and use them directly.

01

Route a process-delay question to the process mapper

Route a process-delay question to the process mapper Use for: Route a process-delay question to the process mapper. Prepare: A bounded operations question, relevant exports, a decision owner, and the complete business-operations Skill collection.

Show prompt and variablesHide prompt and variables
Use the installed business-operations-skills Skill. Task: Route a process-delay question to the process mapper. Inputs: [INPUT]. Constraints: [CONSTRAINTS]. Check missing information first. Produce a reviewable result with evidence, assumptions, and next steps. The router has no analysis scripts of its own; sibling Skills supply them. It is not an ERP and does not approve process or vendor changes.

Replace these variables

[INPUT]
A bounded operations question, relevant exports, a decision owner, and the complete business-operations Skill collection.
[CONSTRAINTS]
Scope, allowed actions, output format, and review requirements.
02

Route a renewal question to vendor or procurement review

Route a renewal question to vendor or procurement review Use for: Route a renewal question to vendor or procurement review. Prepare: A bounded operations question, relevant exports, a decision owner, and the complete business-operations Skill collection.

Show prompt and variablesHide prompt and variables
Use the installed business-operations-skills Skill. Task: Route a renewal question to vendor or procurement review. Inputs: [INPUT]. Constraints: [CONSTRAINTS]. Check missing information first. Produce a reviewable result with evidence, assumptions, and next steps. The router has no analysis scripts of its own; sibling Skills supply them. It is not an ERP and does not approve process or vendor changes.

Replace these variables

[INPUT]
A bounded operations question, relevant exports, a decision owner, and the complete business-operations Skill collection.
[CONSTRAINTS]
Scope, allowed actions, output format, and review requirements.
03

Return an operations digest with findings and owners

Return an operations digest with findings and owners Use for: Return an operations digest with findings and owners. Prepare: A bounded operations question, relevant exports, a decision owner, and the complete business-operations Skill collection.

Show prompt and variablesHide prompt and variables
Use the installed business-operations-skills Skill. Task: Return an operations digest with findings and owners. Inputs: [INPUT]. Constraints: [CONSTRAINTS]. Check missing information first. Produce a reviewable result with evidence, assumptions, and next steps. The router has no analysis scripts of its own; sibling Skills supply them. It is not an ERP and does not approve process or vendor changes.

Replace these variables

[INPUT]
A bounded operations question, relevant exports, a decision owner, and the complete business-operations Skill collection.
[CONSTRAINTS]
Scope, allowed actions, output format, and review requirements.
07

Worked example: Find the biggest wait between picking and dispatch

A 12-person ecommerce team supplies stage records for order release, picking, packing correction and dispatch to choose its first waiting-time reduction. The synthetic records describe a packing-correction cohort.

Steps and prompt

  1. Prepare the attached business materials, preserving amounts, units, dates and metric definitions.
  2. Our homeware ecommerce fulfillment team takes too long from order release to dispatch. Use the supplied process records to locate the bottleneck, map picking and dispatch handoffs, and calculate work, waiting and rework. Recommend the first intervention with an owner, a practical pilot and a measurable follow-up. The supplied stage summaries describe a packing-correction cohort, so keep cohort estimates separate from whole-store delivery performance.
  3. Submit the exact prompt below. Read the primary deliverable on the right and download all deliverables for the team handoff.

Case input files: business-inputs.zip

Use the business-operations-skills Skill.

Our homeware ecommerce fulfillment team takes too long from order release to dispatch. Use the supplied process records to locate the bottleneck, map picking and dispatch handoffs, and calculate work, waiting and rework. Recommend the first intervention with an owner, a practical pilot and a measurable follow-up. The supplied stage summaries describe a packing-correction cohort, so keep cohort estimates separate from whole-store delivery performance.

The attached business materials are:
- inputs/brief.json
- inputs/intake.md

Deliver a complete result.md report that the operations team can read, plus any finished files needed for this task. Keep supporting calculations and evidence with the deliverables. Write the report in English; use the requested target language for customer-facing copy. The business datasets are fictional examples unless the brief explicitly names a live public website.

What the run produced

The primary file produced by this prompt is shown below in its original language.

Reduce the wait for picking first

Pilot more frequent picking pulls, owned by the Picking and packing lead. The daily picking wave is the largest observed delay in the supplied stage summaries: 480 minutes, versus 240 minutes waiting for dispatch. It accounts for 61.5% of the additive time estimate and two-thirds of waiting. This makes picking cadence the strongest first intervention to test. The records establish a delay concentration; they do not establish the team's maximum throughput or prove that staffing is insufficient.

These are fictional stage summaries for a 12-person homeware merchant's selected packing-correction cohort; no operational change or measured improvement has occurred.

What the numbers support

The scope starts with releasing an order and ends when its shipment is dispatched. Carrier transit and customer delivery are outside the records. Every order in this cohort needs packing correction; it is not a representative sample of all store orders.

Time componentSum of stage mediansShare of additive estimateSum of stage P90 values
Input-classified value-add work30 min3.85%60 min
Waiting720 min92.31%2,160 min
Packing correction30 min3.85%90 min
Total780 min / 13 hours100%2,310 min / 38.5 hours

Active work, including correction, totals 60 minutes in the median-stage estimate. Correction therefore consumes 50% of active work, even though it accounts for only 3.85% of elapsed time in this model. Neither percentage is a storewide defect rate.

These totals are sums of stage percentiles. Adding medians does not recover the median of complete orders; adding P90 values does not recover their P90. Use 13 hours as an additive planning estimate and 38.5 hours as a stage-P90 scenario, not customer promises or observed end-to-end service levels. Order-level event records are needed for actual end-to-end percentiles. The supplied value-add classifications are retained, rather than independently validated.

The analyzer labels the process WASTE-HEAVY because its value-add share is 3.85%. Its actual services profile uses 8% and 20% boundaries. These are tool heuristics, not a retail fulfillment benchmark. The requested services profile is retained because the package has no retail profile.

The tool also outputs 0.6154 items/hour from 8 ÷ (780 ÷ 60). That is only an arithmetic proxy: eight is a WIP snapshot, and 780 is an additive median-stage estimate. Little's Law requires a consistent stable system boundary, average WIP and mean elapsed time over a comparable period. The inputs cannot establish actual throughput, daily capacity, a staffing requirement or a whole-store delivery rate.

Current correction-cohort process

Each box shows the supplied stage median. Solid arrows show internal sequence and handoffs within the same operation.

flowchart LR
    start((Start)) --> release
    subgraph release_lane[Order release coordinator]
        release["1. Release fulfillment order · Work · 10 min"]
    end
    subgraph picking_lane[Picking and packing lead]
        pickwait["2. Wait for picking wave · Wait · 480 min"]
        pickpack["3. Pick and pack order · Work · 15 min"]
        correction["5. Correct packing mismatch · Rework · 30 min"]
    end
    subgraph dispatch_lane[Dispatch lead]
        dispatchwait["4. Wait for dispatch handoff · Wait · 240 min"]
        dispatch["6. Dispatch shipment · Work · 5 min"]
    end
    release --> pickwait --> pickpack --> dispatchwait
    dispatchwait -->|Return for correction| correction
    correction -->|Corrected order| dispatch --> finish((Dispatched))
HandoffReceiving roleSupplied delay and implication
Released order → pickingPicking and packing leadMedian 480 min; P90 1,440 min. Picking happens once daily, despite batch size 1 after release.
Packed order → dispatch handoffDispatch leadMedian 240 min; P90 720 min. Queue ownership and dispatch coverage need checking.
Dispatch handoff → packing correctionPicking and packing leadCorrection median 30 min; P90 90 min. A separate return-queue wait is not supplied.
Corrected order → dispatchDispatch leadDispatch work median 5 min; P90 10 min. A separate second handoff wait is not supplied.

This is the supplied correction route, including its return to packing. The records do not describe a no-correction route, repeated correction loops or their frequencies. The pilot should record any additional queues rather than assuming they take zero time.

Ranked diagnosis

PriorityEvidence and detector resultOperational interpretation
1. Picking-wave wait480 min; CRITICAL, R1. It is 48 times the 10-minute mean of value-add stages.Once-daily cadence is documented. Test whether additional pulls shorten waiting; verify staffing and release timing before treating batching as the sole cause.
2. Dispatch-handoff wait240 min; CRITICAL, R1. It is 24 times that mean.A second large queue can absorb the gains from faster picking. A batch or coverage mismatch is a hypothesis; dispatch schedule and queue-age records are missing.
3. Packing correction30 min; MEDIUM, R1. It exceeds the services stage threshold of 25 min.Correction is material labor within this cohort. Missing or incorrect packing information is only a hypothesis; record reason codes before choosing an upstream prevention change.

R2 separately flags combined waiting as HIGH, at 92.31% against a 50% threshold. This overlaps the two wait stages: do not add its 720 minutes to their 480 and 240 minutes. R3 does not trigger because rework's elapsed-time share is below its 15% threshold; that does not establish acceptable quality. The raw detector's approval and self-service suggestions are generic possibilities, not findings about this fulfillment team.

This prioritization follows the supplied Theory of Constraints guidance to act on the dominant constraint first, the value-stream guidance to separate waiting from work, and the bottleneck anti-pattern guidance on batch delays and local optimization. Method and evidence

First intervention: a short picking-cadence pilot

Owner: Picking and packing lead. Accountable role: Operations manager, proposed for end-to-end review. The Order release coordinator maintains complete event records; the Dispatch lead checks downstream queues and cutoffs. Role titles describe responsibilities and do not assume new hires.

  1. Establish a comparable baseline over five staffed days. Log every eligible released order, including orders still open at the end. Use the existing cadence and record staffing, order complexity, dispatch cutoffs and the starting open-order inventory. Calculate order-level medians and P90s; retain correction and no-correction subsets separately.
  2. Run ten staffed days with a scheduled pull every two staffed hours. Keep the same staffing and per-order batch size. Pick the oldest eligible released order at each pull. Before starting, the two leads write down existing staffed hours and dispatch acceptance cutoffs; fit pulls inside that coverage and identify the final feasible pull. Overnight waits remain part of elapsed time. If current coverage cannot support the proposed cadence, record the constraint and revise the schedule before starting.
  3. Review queues at each pull and at shift end. Record missed pulls and reasons. The Dispatch lead watches the packed-order queue so work does not simply accumulate downstream. Continue the existing correction path; log its time and reason. Do not infer a quality gain from this cadence change.
  4. Review after pilot day 5 and decide after day 10. Compare with baseline by weekday, release window and order complexity. Report sample sizes, incomplete orders and changes in volume or staffing. If sparse data or changed mix makes the comparison unreliable, extend observation instead of claiming success.

The primary goal is a 50% reduction in measured picking-wait median versus the matched baseline. The supplied 480-minute median gives a provisional 240-minute reference. The primary business check is improved measured release-to-dispatch median across all eligible orders, with no increase in its P90. Report the correction cohort alongside that whole-pilot population; cohort membership can change, so it cannot serve as the only success measure.

Adopt the cadence only if dispatch-wait median and P90, dispatch-cutoff miss rate, packing-correction frequency and correction labor do not worsen versus the matched baseline, and there is no additional paid staffing or growing backlog. Review labor minutes per order by volume and complexity. A cutoff or quality problem attributable to the cadence triggers review and reversion to the prior cadence while the cause is investigated. Use the pilot scorecard to record the decision; its result cells are intentionally blank.

As an illustration only, reducing picking wait from 480 to 240 minutes while holding every other median constant reduces the additive estimate from 780 to 540 minutes, a 240-minute / 30.77% reduction. This is a planning scenario, not a predicted or achieved improvement. Dispatch waiting would then equal picking waiting, making the next constraint review necessary.

Measurement and completed supporting files

Use pilot-event-log.csv and its event definitions to log pseudonymous order references, event times, actual roles, correction attempts and labor minutes. Compute end-to-end percentiles from each order's own timestamps, count open orders separately, and measure throughput directly as completed shipments per staffed hour. No carrier-delivery outcome is available here.

The current process map and normalized process data preserve the six stages. calculations.csv contains the formulas and exact quantities; tool-cycle-time.json and tool-bottlenecks.json preserve the original tools' outputs with their interpretation explained in evidence.md. verify-calculations.py independently checks those results.

Before scaling, the Operations manager should resolve one decision challenge: if picking wait falls but release-to-dispatch time does not, which downstream queue grew, and should the next intervention move there? This follows the supplied Theory of Constraints instruction to repeat the constraint assessment after each change.

Merchant business data is synthetic. Website observations, when present, come from the public URLs listed in the report.

08

Risks and operating notes

Known limits

The router has no analysis scripts of its own; sibling Skills supply them. It is not an ERP and does not approve process or vendor changes.

Evidence and review

Source and package files reviewed: GitHub 6d2f02ea077e. This is a static review, not an installation or business-outcome test.

Before acting on the result

Use authorized inputs and keep secrets out of prompts. Review customer-facing claims, calculations, code changes, and any proposed external action before applying them.

Frequently asked questions

What does it do, and what is the advantage?

Route internal operations questions to six specialist workflows and return a concise decision brief. The router distinguishes process, vendor, capacity, communications, knowledge, and procurement work before selecting a lane.

How do I install it and start?

Choose the method for your agent and install the complete package, not just the displayed SKILL.md. A bounded operations question, relevant exports, a decision owner, and the complete business-operations Skill collection. Start a new agent session and explicitly ask to use business-operations-skills. Try one use case below with a small sample and review the output.

Which situations is it useful for?

Route a process-delay question to the process mapper; Route a renewal question to vendor or procurement review; Return an operations digest with findings and owners

What limitations should I know?

The router has no analysis scripts of its own; sibling Skills supply them. It is not an ERP and does not approve process or vendor changes.

What was checked for this page?

Source and package files reviewed: GitHub 6d2f02ea077e. This is a static review, not an installation or business-outcome test.

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Author / maintainer

Alireza Rezvani

Source and package files reviewed: GitHub 6d2f02ea077e. This is a static review, not an installation or business-outcome test.