nicholashidalgo executive-summary-writer
Purpose: Take a full report or document and synthesize it into a 150-300 word executive summary that a decision-maker can act on without reading the full document.
Input Schema
| Field | Type | Required |
|---|---|---|
source_title |
string | yes |
source_content |
string | yes - full document or long excerpt |
audience |
string | yes |
key_findings |
string[] | yes - top 3-5 findings to surface |
recommended_actions |
string[] | yes |
preserve_facts |
string[] | yes |
{
"source_title": "Q1 2024 Platform Engineering Report",
"source_content": "...",
"audience": "VP Engineering",
"key_findings": ["CI build time improved 60%", "On-call volume down 40%", "2 critical infra migrations completed"],
"recommended_actions": ["Approve Q2 headcount for observability", "Extend Kubernetes rollout to remaining 12 services"],
"preserve_facts": ["60%", "40%", "12 services", "Q1 2024"]
}
Output Schema
{
"title": "Executive Summary: Q1 2024 Platform Engineering",
"summary": "...",
"findings": ["..."],
"recommended_actions": ["..."],
"word_count": 215
}
Prompt Flow
Pass 1: Three-part structure: What happened (findings), What it means (interpretation in 1-2 sentences), What's next (recommended actions). Remove: P1, P3, P4, P5, P6, P7, P14, P15, P22, P23, P24. Preserve all facts.
Pass 2: "What in this summary is padding?" -> cut aggressively to under 300 words. Every sentence must do work.
Examples
Short - findings sentence
Before: "The platform team has made significant strides, showcasing their commitment to fostering a culture of continuous improvement that underscores their vital role in the organization's evolving landscape." After: "CI build time dropped 60% in Q1; on-call volume fell 40%."
Medium - full summary
Before: "In conclusion, the future looks bright for our platform infrastructure. Exciting times lie ahead as we continue this journey toward excellence and scalability." After: "Q1 work shipped two critical migrations and cut on-call load nearly in half. Q2 priority: extend Kubernetes to the remaining 12 services and hire 2 observability engineers to avoid repeating the January monitoring gap."
Long
Unit Tests
# tests/skills/test_executive_summary_writer.py
from ai_pattern_scrubber import detect_patterns
FINDING = "CI build time dropped 60% in Q1; on-call volume fell 40%."
CLOSE = "Q2 priority: extend Kubernetes to 12 services and hire 2 observability engineers."
def test_finding_no_significance_inflation():
assert not [h for h in detect_patterns(FINDING) if h.id == 1]
def test_close_no_generic_conclusion():
assert not [h for h in detect_patterns(CLOSE) if h.id == 24]
def test_finding_no_high_severity():
assert not [h for h in detect_patterns(FINDING) if h.severity == "high"]