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Html Report

Community
Firstp1ck
html-report

Creates polished self-contained HTML explanation reports for complex, multi-step topics using overview tables, evidence cards, adaptive graphs or diagrams, meaningful SVG/media, and accessible tabs for long pages. Use when the user requests a browser-readable diagnostic report, technical guide, decision analysis, implementation plan, investigation, or research synthesis as HTML.

Overview

PublisherFirstp1ck
Repositorypi-coding-agent-forge
Skill namehtml-report
Stars
93
Forks
22
Bundled files
8
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.

  • 8 bundled files

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

  • Open source

    Published by Firstp1ck on GitHub. Read the source before you install it.

Installation

Install the Html 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/Firstp1ck/pi-coding-agent-forge/tree/main/pi-skill-html-report/skills/html-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/Firstp1ck/pi-coding-agent-forge.git /tmp/pi-coding-agent-forge
mkdir -p .claude/skills
cp -r /tmp/pi-coding-agent-forge/pi-skill-html-report/skills/html-report .claude/skills/html-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Html 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 Html 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 Html 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.

HTML Report

Create source-grounded, browser-readable explanation reports with the approved dark navy visual system. The output is a document, not an application: it should open locally without a build step, remain understandable when printed, and use visuals only when they clarify real information.

When to Use

Use this skill when both are true:

  • The user requests an HTML page/report or clearly wants a browser-readable artifact.
  • The subject is complex or multi-step: diagnostics, investigations, implementation guidance, architecture, technical decisions, comparisons, research synthesis, or operational plans.

Do not use it for:

  • Short answers that do not warrant a file.
  • Slide presentations; use a presentation-specific skill instead.
  • Product dashboards, landing pages, or application UI implementation.
  • A generic technology comparison unless the user requests an HTML report.
  • Content whose evidence is too incomplete to explain responsibly; collect evidence or mark uncertainty first.

Should trigger

  • “Create a self-contained HTML report explaining this multi-stage incident with evidence, diagrams, and recommendations.”
  • “Turn this architecture analysis into a polished browser-readable explanation.”
  • “Make an HTML implementation guide with a process diagram, overview, risks, and phased steps.”
  • “Research these options and deliver a detailed HTML decision document.”

Should not trigger

  • “Explain this error in three bullets.”
  • “Build an interactive product analytics dashboard.”
  • “Create a 16:9 HTML slide deck.”
  • “Compare React and Vue and recommend one.”

Invocation Design

  • Invocation mode: model-invoked after the package is explicitly enabled.
  • Leading concept: HTML explanation report.
  • Trigger branches:
    1. Complex or multi-step explanation explicitly requested as HTML.
    2. Technical diagnostic, guide, analysis, investigation, or synthesis needing a standalone browser report.
  • The package is a disabled draft until the user explicitly installs/enables it; creation alone must not modify Pi settings.

Inputs and Assumptions

Collect, as available:

  • Source notes, logs, files, command output, research, and citations.
  • The real question, audience, success criteria, and requested output path.
  • Quantitative data suitable for charts and relationship/process data suitable for diagrams.
  • User-provided local images or approved media. Do not assume remote assets are allowed.
  • Existing HTML or project conventions if the report belongs to a repository.

If the user does not specify a filename, use a concise descriptive name ending in .html. Preserve uncertainty and distinguish observed facts, documentation, interpretation, and recommendations.

Portable Workflow

  1. Establish the evidence model

    • Identify the question, audience, claims, sources, uncertainty, and recommended actions.
    • Do not invent measurements, graph values, timelines, citations, or visual relationships.
    • Completion criterion: every major claim is traceable to supplied/verified evidence or explicitly labeled as interpretation.
  2. Plan the information architecture

    • Build a section map before writing. Include a hero summary, mandatory overview table, main explanation, actionable steps, evidence/source notes, and limitations.
    • Read references/CONTENT-ARCHITECTURE.md when the page has multiple audiences, branches, or more than five major sections.
    • Completion criterion: the outline has one clear reading path and no duplicated sections.
  3. Select visuals deliberately

    • Use the matrix in references/VISUAL-DECISIONS.md.
    • Add a graph for real quantitative comparisons/trends; a diagram for flows, dependencies, decisions, or architecture; and meaningful inline SVG/local media where spatial context helps.
    • If no visual materially improves comprehension, omit it and keep the layout strong rather than adding decoration.
    • Completion criterion: each visual has a stated explanatory purpose, accessible text, and source/provenance where applicable.
  4. Choose interaction and long-page navigation

    • Read references/INTERACTION-DESIGN.md and name the reader task served by each proposed interaction.
    • Use accessible tabs when there are at least six major sections, roughly 2,500+ words, multiple independent reading paths, or excessive scrolling. For shorter reports, prefer normal sections and optional anchor navigation.
    • Add task-focused controls where they reduce friction: in-report search with highlighted matches, reading progress, optional focus mode, sequential previous/next navigation, session-only section completion, copy buttons for reusable commands or exact excerpts, expand/collapse controls for several disclosure blocks, print or deep-link actions, and filtering only for genuinely large tables.
    • Keep the executive conclusion and overview visible by default. Use native controls, keyboard support, visible focus, status announcements, URL hashes where relevant, and print rules that reveal content while suppressing meaningless controls.
    • Preserve progressive enhancement: the complete report must remain readable, selectable, and navigable when JavaScript, clipboard access, or optional interaction fails.
    • Completion criterion: every interaction has a clear purpose, works without pointer input, communicates its result, and leaves all essential content available without script enhancement and in print.
  5. Apply the approved design system

    • Read references/DESIGN-SYSTEM.md and start from assets/starter-template.html when practical.
    • Preserve the navy radial background, rounded dark panels, blue-gray borders, restrained shadows, high-contrast typography, and semantic status colors.
    • Use metric cards, evidence tables, prioritized findings, numbered steps, callouts, and collapsible detail only where they fit the content.
    • Completion criterion: the report is visually coherent at desktop and mobile widths and does not depend on an external CDN.
  6. Generate the self-contained report

    • Prefer one HTML file with embedded CSS and minimal JavaScript. Inline SVG is preferred for custom charts and diagrams.
    • Local image files are acceptable when supplied or generated; use relative paths and meaningful alt text. Ask before overwriting user-authored output.
    • Treat the starter template placeholders as scaffolding and replace/remove all of them.
    • Completion criterion: the file opens directly in a browser, contains no unresolved placeholders, and has no missing local dependencies.
  7. Verify and report

    • Run the bundled validator from the skill directory:
bash
python3 ./scripts/validate_report.py <path-to-report.html> --strict
  • Also inspect the report at narrow/mobile width and print preview when browser tooling is available.
  • Completion criterion: validation passes, intentional warnings are disclosed, and the final response includes a clickable Markdown link to the report plus any unverified rendering caveat.

Output Contract

The final assistant response must always end with a standalone clickable Markdown link to the generated report, using the report filename as the label and its absolute path as the target:

markdown
[report-name.html](/absolute/path/to/report-name.html)

Do not provide only a plain-text path or wrap the link in a code block. Keep this link as the final non-empty line so it is easy to find and click.

Every generated report must include:

  • A descriptive document title, language, viewport metadata, and semantic landmarks.
  • A concise hero conclusion and scope/context.
  • An overview table summarizing sections, findings, stages, options, or recommendations.
  • Source-grounded narrative with uncertainty/confidence where relevant.
  • Prioritized, actionable recommendations or next steps.
  • Responsive and print CSS.
  • References/evidence and limitations when claims depend on external or incomplete information.

Conditional components:

  • Graphs only for quantitative data.
  • Diagrams only for meaningful relationships or sequences.
  • Images/SVG only when they improve comprehension.
  • Tabs only when page length or independent reading paths justify them.
  • Interactive controls only when they serve a concrete reader task; prefer native elements and progressive enhancement.
  • Search, progress, focus, sequential navigation, completion, copy, disclosure, filtering, view, print, or deep-link controls only when their targets and fallback behavior remain useful without JavaScript.

Scripts, References, and Dependencies

Bundled resources, relative to this skill directory:

  • assets/starter-template.html — self-contained report shell with overview table, accessible tabs, graph, diagram, responsive layout, and print behavior.
  • references/DESIGN-SYSTEM.md — visual tokens and component contract.
  • references/CONTENT-ARCHITECTURE.md — section planning and tab thresholds.
  • references/VISUAL-DECISIONS.md — graph/diagram/media selection, accessibility, and data integrity.
  • references/INTERACTION-DESIGN.md — purposeful controls, progressive enhancement, accessibility, privacy, and interaction verification.
  • scripts/validate_report.py — standard-library Python validator for generated reports.
  • tests/ — package contract tests and representative fixtures.

No runtime package or browser build dependency is required.

Verification

For this package:

bash
cd <package-root>
npm test

For a generated report:

bash
cd <skill-directory>
python3 ./scripts/validate_report.py <path-to-report.html> --strict

Success means: valid core structure, overview table present, local assets resolved, no placeholders, image/SVG accessibility checks passed, tab wiring valid when tabs exist, long pages tabbed, and responsive/print rules detected.

Quality Review

Before delivery, confirm:

  • The routing scope is not confused with slide decks, dashboards, or short prose answers.
  • The overview table gives a useful map rather than repeating headings mechanically.
  • Every visual communicates evidence; no decorative chart junk or fabricated values exist.
  • Tabs reduce cognitive load without hiding critical conclusions.
  • Every other interaction serves a named reader task, uses semantic controls, reports outcomes, and degrades without hiding content.
  • Long reference material stays in references/, not duplicated in this file.
  • No private paths, secrets, stale source-report content, or user-specific facts were copied into the reusable package.

Safety and Failure Modes

  • Ask before overwriting an existing user-authored report or changing files outside the requested output scope.
  • Do not embed secrets, private logs, personal data, or unredacted sensitive evidence in a shareable report.
  • Do not hotlink external images, scripts, fonts, or styles unless the user approves the privacy and availability trade-off.
  • Never turn qualitative statements into quantitative graphs without real values.
  • If SVG complexity harms accessibility, replace it with a simpler diagram plus a text/table equivalent.
  • If tabs fail validation, fall back to ordinary semantic sections rather than shipping inaccessible navigation.
  • If copy, filtering, disclosure, or other enhancements fail, keep the underlying text and controls' targets directly usable; remove dead controls rather than making content script-dependent.
  • Do not add telemetry, persistence, network-backed widgets, auto-advancing content, or copied sensitive data as interaction polish.
  • If evidence is contradictory or incomplete, show the conflict and lower confidence; do not manufacture a single definitive story.

Pi Adapter

  • Use Pi file-reading and repository exploration tools to gather evidence before drafting.
  • Use write for a new self-contained report and edit for targeted changes to an existing report.
  • For multi-step creation, use Pi's todo progress UI and verify the final path.
  • End the final response with the standalone Markdown report link required by the Output Contract; use the verified absolute file path as the link target.
  • Do not install this local package or modify Pi settings without explicit user confirmation.

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 Html Report AI skill do?

Creates polished self-contained HTML explanation reports for complex, multi-step topics using overview tables, evidence cards, adaptive graphs or diagrams, meaningful SVG/media, and accessible tabs for long pages. Use when the user requests a browser-readable diagnostic report, technical guide, decision analysis, implementation plan, investigation, or research synthesis as HTML.

Why use Html Report on TypingMind?

Because you install it once and use it with any model. Html 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 Html Report in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Firstp1ck/pi-coding-agent-forge/tree/main/pi-skill-html-report/skills/html-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 Html 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 Html Report?

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

Is the Html Report AI skill free?

Yes. It is published on GitHub by Firstp1ck 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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