Exec Report logo

Exec Report

Organization
pnp
exec-report

Generates a polished, self-contained HTML executive report or dashboard from any data source — SharePoint lists, CSV exports, or a user description. Use when asked to build an exec report, one-pager, summary page, status dashboard, project summary, business review, or any single-page visual summary of data. Interviews the user if data is incomplete, constructs a validated JSON document block by block, then renders it into a single sandbox-safe HTML file using the component library. No external dependencies — output runs inside a SharePoint sandboxed iframe.

Overview

Publisherpnp
Repositorysharepoint-skills
Skill nameexec-report
Stars
141
Forks
60
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by pnp on GitHub. Read the source before you install it.

Installation

Install the Exec Report AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/pnp/sharepoint-skills/tree/main/Skills/exec-report/exec-report
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/pnp/sharepoint-skills.git /tmp/sharepoint-skills
mkdir -p .claude/skills
cp -r /tmp/sharepoint-skills/Skills/exec-report/exec-report .claude/skills/exec-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Exec Report in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Exec Report on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Exec Report is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Exec Report

Generates a complete, self-contained HTML report by (1) interviewing the user or parsing their data, (2) constructing and validating a JSON document, then (3) rendering that JSON into HTML using assets/report-template.html. The JSON is the authoritative source of truth; the HTML is fully determined by it.


Step 1: Determine the Data Source

Check what the user has already provided before asking anything:

  • SharePoint lists: Call list_items on the relevant lists. Read all needed columns before proceeding.
  • CSV or table pasted in chat: Parse all rows. Do not ask for data you already have.
  • Verbal description only: Proceed to Step 2.

Step 2: Interview the User

If the data or intent is not fully clear, ask these questions in a single message — not one at a time:

  1. Topic: What is this report about? (e.g., "Q2 pipeline health," "IT project status," "department spend overview")
  2. Audience: Who is reading it? Exec team, department head, all-hands? This determines detail level.
  3. Narrative intent: What is the shape of the story? Pick the closest match:
    • Achievement — "we hit a goal, here's how" (lead with the win: kpi-row + trend dominate)
    • Problem — "something needs attention, here's what" (lead with urgency: status-grid or table comes first)
    • Status — "here's where everything stands" (balanced overview: status-grid early, kpi-row supporting)
  4. Headline message: What should the reader walk away knowing? This becomes the hero sentence — one sentence.
  5. Sections wanted: Any specific sections — comparison to prior period, breakdown by category, status of open items, narrative highlights?
  6. Palette: Warm paper (cream/terra-cotta), deep ink (dark/gold), clean white (white/green), or slate (gray/blue)? Default to warm paper if no preference.

If the user's prompt already signals narrative intent (e.g., "the headline is the gap," "lead with urgency," "show the wins"), skip question 3 — you already have the answer.

Confirm your understanding before building the JSON.


Step 3: Choose Components and Narrative Order

The component sequence IS the story. Read references/components.md for the full component catalog, props schemas, and HTML patterns.

Always true:

  • Open with hero — sets the company, label, and hero sentence.
  • Close with highlights — narrative "so what" belongs last.
  • Maximum one trend, one table, and one highlights per report.
  • Keep total block count to 4–8.

Narrative intent drives the block order:

IntentTypical sequenceHero sentence shape
Achievementhero → kpi-row → trend → bar-list → compare → status-grid → highlights"We closed $X, up Y% from last quarter."
Problemhero → status-grid → compare → table → bar-list → highlights"We enter Q3 with X open roles and a gap in Y."
Statushero → status-grid → kpi-row → compare → bar-list → highlights"Here's where all six workstreams stand heading into Q3."

The hero sentence signals intent to the reader. Achievement heroes lead with a number and a direction. Problem heroes lead with a situation. Status heroes lead with a scope statement.

Component selection guide:

Data shapeComponent
2–4 headline numbers worth celebrating or trackingkpi-row
Values over time (3+ periods)trend
Category breakdown with relative sizesbar-list
Structured numeric comparison (QoQ, YoY, plan vs. actual)compare
Detailed row data (5+ items with 3+ fields)table
Health or urgency status of multiple itemsstatus-grid
Narrative insights: bright spots, risks, actionshighlights

Hard rules:

  • Never put a headline number in prose when kpi-row can show it larger.
  • Never use table for 2–4 numbers — use kpi-row.
  • kpi-row is not mandatory — omit it when the story is problem- or urgency-forward and metrics are supporting context, not the lead.

Step 4: Build and Validate the JSON Document

Construct the JSON object. Top-level structure:

report object (document metadata):

FieldRequiredDescription
paletteyeswarm-paper, deep-ink, clean-white, or slate
footer_lnoLeft footer text, e.g. "Generated May 28, 2026"
footer_rnoRight footer text, e.g. "47 deals analyzed"

blocks array — ordered list of content blocks. Each block: type string + props object. See references/components.md for every component's full props schema.

Validation Checklist

Run every check before rendering. Fix any failure before proceeding.

Document level:

  • report.palette is one of: warm-paper, deep-ink, clean-white, slate
  • blocks array has at least one entry
  • First block type is hero
  • Last block type is highlights
  • Block order reflects the declared narrative intent (achievement / problem / status)

Per block:

  • type is one of: hero, kpi-row, trend, bar-list, compare, table, status-grid, highlights
  • All required props are present (see components.md)
  • Numeric values are numbers, not strings with embedded units
  • No block exceeds its item count limits (see components.md limits table)

Data integrity:

  • kpi-row items count is 2–4
  • bar-list shares: largest item = 1.0, all others ≤ 1.0
  • trend data and labels arrays have the same length (3–12)
  • trend prior_data (if present) same length as data
  • compare rows have dir set to "up" or "down" on every row
  • table headers count matches every row's cell count
  • highlights items count is 3–5

Step 5: Render the HTML

  1. Read assets/report-template.html.
  2. Replace {{REPORT_TITLE}} in <title> with a concise page title (company + report label).
  3. Replace {{PALETTE_CLASS}} on <body> with palette- + the palette name (e.g. palette-warm-paper).
  4. Generate the hero block HTML (.rpt-header + .hero) and replace {{HERO}}.
  5. Generate all remaining blocks in order and replace {{BLOCKS}}.
  6. Replace {{FOOTER_L}} and {{FOOTER_R}} with footer text (or empty strings).
  7. Generate the {{INLINE_SCRIPT}} content. Include:
    • Segment bar fill-in code (if any bar-list blocks are present)
    • Trend tooltip JS with embedded TREND_DATA array (if a trend block is present)
    • See the template's script comment block for the exact code patterns to use.
  8. Deliver the complete file as the response. No prose outside the file.

If the site context specifies a folder for report output, save the file there after delivering it.


Hard Constraints

  • No external URLs, CDN links, or web fonts in the output HTML.
  • No <script src> tags. All JavaScript must be inline.
  • All data values must be pre-rendered into the HTML — the page must be fully correct with JavaScript disabled. JS adds animations and tooltips but must never be required for correctness.
  • Do not generate Python, PowerShell, or any other scripts — output is always the HTML file.
  • Do not render until the validation checklist passes.
  • Follow the no-Person-column-type rule for any accompanying SharePoint schema: use text columns only.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Exec Report AI skill do?

Generates a polished, self-contained HTML executive report or dashboard from any data source — SharePoint lists, CSV exports, or a user description. Use when asked to build an exec report, one-pager, summary page, status dashboard, project summary, business review, or any single-page visual summary of data. Interviews the user if data is incomplete, constructs a validated JSON document block by block, then renders it into a single sandbox-safe HTML file using the component library. No external dependencies — output runs inside a SharePoint sandboxed iframe.

Why use Exec Report on TypingMind?

Because you install it once and use it with any model. Exec Report is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Exec Report in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/pnp/sharepoint-skills/tree/main/Skills/exec-report/exec-report. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Exec Report?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Exec Report?

As many as you like. As long as a model supports skills, you can use Exec Report with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Exec Report AI skill free?

Yes. It is published on GitHub by pnp under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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