department-synthesizer

department-synthesizer is a skill for Claude Code from nickstellarstreamai/ai-opportunity-finder. It costs 58 tokens per session (1,881 once invoked), scanned A, original, MIT.

A method for combining findings from multiple interviews in one department into a shared view of its problems and opportunities.

In plain words
What is it for?
Use it after at least two interview analyses to inventory pain points, quantify their effect, and create a department-level synthesis.
Why use it?
It helps distinguish an isolated complaint from a repeated department-wide pattern. It also combines the findings to estimate total impact and separate quick improvements from larger initiatives.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the ai-opportunity-finder plugin — 7 skills shipped together

Good fit Use it after at least two interview analyses to inventory pain points, quantify their effect, and create a department-level synthesis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nickstellarstreamai/ai-opportunity-finder/department-synthesizer
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.

Any agent
npx skills add nickstellarstreamai/ai-opportunity-finder --skill department-synthesizer
Clone the repo
git clone --depth 1 https://github.com/nickstellarstreamai/ai-opportunity-finder

Made for: Claude Code.

Or install ai-opportunity-finder, the plugin that ships this one along with the rest of its 7 skills.

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 department-synthesizer

README.md
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Your own site
<a href="https://agentmods.dev/skills/nickstellarstreamai/ai-opportunity-finder/department-synthesizer"><img src="https://agentmods.dev/badge/skills/nickstellarstreamai/ai-opportunity-finder/department-synthesizer/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.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/nickstellarstreamai/ai-opportunity-finder/department-synthesizer"><img src="https://agentmods.dev/badge/skills/nickstellarstreamai/ai-opportunity-finder/department-synthesizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,881 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00058 $0.01881
Opus 5 $0.00029 $0.00941
Sonnet 5 $0.00012 $0.00376
Haiku 4.5 $0.00006 $0.00188

Measured 12d ago against content hash 4bd11bf10340, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

department-synthesizer 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 12d 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.

skills/department-synthesizer/SKILL.md · 230 lines

How it starts

The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Department Synthesizer

Takes multiple interview findings documents (from /insight-analyzer) for a single department and synthesizes them into one consolidated view. This is where individual data points become organizational patterns — where "one person complains about scheduling" becomes "scheduling costs this department 800 hours/year."

Why This Matters

Individual interviews are interesting. Synthesis is where the money is.

When 3 people in the same department independently describe the same frustration, that's no longer an opinion — it's a validated organizational problem. This skill does that triangulation for you.

What I Need From You

  1. Department name
  2. 2 or more Interview Findings documents (output from /insight-analyzer)
    • Provide as file paths or paste the content directly
  3. Survey data (optional — if you ran a pre-interview survey)
  4. Any additional context about the department (headcount, budget, strategic importance)

What You'll Get

A Department Synthesis Document — the definitive view of one department's AI opportunities.

Processing Logic

When I receive the findings, I:

  1. Inventory all pain points across all interviews
  2. Triangulate — Flag any pain point mentioned by 2+ people as validated
  3. Aggregate quantification — Sum hours across interviewees, calculate department-wide impact
  4. Identify root causes — Connect surface-level complaints to underlying systemic issues
  5. Categorize opportunities — Quick Wins (2-8 weeks, low complexity) vs Strategic (2-6 months, higher complexity)
  6. Score each opportunity on Impact and Feasibility

Output Format

# Department Synthesis: [Department Name]
**Company:** [Company Name]
**Date:** [Date]
**Interviews Analyzed:** [Number]
**Interviewees:** [Names and roles]

---

## Main Insight

[ONE powerful sentence that captures the core finding for this department.]

Format: "[Department] spends [X hours/year] on [activity] that [impact statement]."

---

## Core Problem

**What's fundamentally broken:**
[2-3 sentence description of the systemic issue — not just symptoms, but the underlying problem]

**Validated by:**
| Source | Evidence |
|--------|----------|
| [Name, Role] | "[Quote or finding]" |
| [Name, Role] | "[Quote or finding]" |
| [Name, Role] | "[Quote or finding]" |

**Confidence Level:** [High (3+ sources) / Medium (2 sources) / Low (1 source + inference)]

---

## Why It's Happening

**Root Cause 1:** [Description]
- Evidence: [What points to this cause]

**Root Cause 2:** [Description]
- Evidence: [What points to this cause]

**Root Cause 3:** [Description]
- Evidence: [What points to this cause]

---

## Quantified Impact

### Time Burden

| Process/Activity | Source | Hours/Week | Hours/Year | People |
|-----------------|--------|------------|------------|--------|
| [Activity 1] | [Who reported it] | [X] | [X × 50] | [N] |
| [Activity 2] | [Who reported it] | [Y] | [Y × 50] | [N] |
| **Total** | | **[Sum]** | **[Sum]** | |

### Cost Estimate

| Category | Annual Hours | Cost at $50/hr | Cost at $75/hr |
|----------|-------------|----------------|----------------|
| Manual processes | [X] | $[Amount] | $[Amount] |
| Rework/errors | [Y] | $[Amount] | $[Amount] |
| Coordination overhead | [Z] | $[Amount] | $[Amount] |
| **Total** | **[Sum]** | **$[Sum]** | **$[Sum]** |

*Note: $50/hr is a conservative estimate for staff time. Adjust based on your actual loaded labor costs.*

### Quality & Risk Impact

- [Error rate or quality issue mentioned]
- [Risk identified (e.g., single point of failure, knowledge loss)]
- [Downstream impact on other departments]

---

## Opportunities

### Quick Wins (2-8 weeks, Low Complexity)

**1. [Opportunity Name]**
| Dimension | Detail |
|-----------|--------|
| **Description** | [What to build or change] |
| **Impact** | [Hours saved/year, $ value] |
| **Complexity** | Low |
| **Dependencies** | [What needs to be true] |
| **Validated by** | [Which interviewees support this] |
| **Why it's a quick win** | [Low technical complexity, data available, champion exists] |

**2. [Opportunity Name]**
...

### Strategic Initiatives (2-6 months, Medium-High Complexity)

**3. [Opportunity Name]**
| Dimension | Detail |
|-----------|--------|
| **Description** | [What to build or change] |
| **Impact** | [Hours saved/year, $ value] |
| **Complexity** | Medium / High |
| **Dependencies** | [What needs to be true — integrations, data, change management] |
| **Validated by** | [Which interviewees support this] |
| **Why it's strategic** | [Requires more investment but delivers transformational value] |

---

## Cross-Interview Patterns Detected

| Pattern | # of Sources | Confidence | Evidence |
|---------|-------------|------------|----------|
| [Pattern name] | [N] | [High/Med/Low] | [Brief evidence summary] |
| [Pattern name] | [N] | [High/Med/Low] | [Brief evidence summary] |

**Patterns appearing in 3+ interviews are high confidence and should be treated as organizational facts, not opinions.**

---

## Implementation Considerations

**Prerequisites:**
- [Data access needed]
- [System integrations required]
- [Stakeholder buy-in needed]

**Risks:**
- [Risk 1] — Mitigation: [How to address]
- [Risk 2] — Mitigation: [How to address]

**Success Factors:**
- [What needs to be true for this to work]
- [Who needs to champion this internally]

**Change Management Notes:**
- [How receptive were interviewees to change?]
- [Any resistance signals to watch for?]

---

## Department Summary Card

| Metric | Value |
|--------|-------|
| Total addressable hours/year | [X] |
| Estimated annual cost | $[Y] |
| Quick win opportunities | [N] |
| Strategic opportunities | [N] |
| Confidence level | [High/Medium/Low] |
| Top priority | [Opportunity name] |

---

## Next Steps

1. Run `/department-synthesizer` for other departments
2. Once all departments are synthesized, run `/priority-ranker` to compare across the organization
3. Use the Main Insight and Key Quotes in your `/executive-briefing`

---
Built with the AI Opportunity Finder by Morningside AI
Want expert help? → https://morningside.ai

Read the full file on GitHub · 230 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. 12d ago First seen · 230 lines · 58 tokens per session scan A 4bd11bf10340

Subscribe to this mod's changes

department-synthesizer is a skill published in the GitHub repository nickstellarstreamai/ai-opportunity-finder (11 stars, last pushed 5mo ago), licensed MIT. It adds 58 tokens to every session and 1,881 once invoked, about $0.0003 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 2026-08-30.

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