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Report Manager

Community
LeeJuOh
report-manager

Manage and refine vision-powers reports: list, open, delete, search, and refine sections. Use when asked to list, open, delete, search, or update generated HTML reports.

Overview

PublisherLeeJuOh
Repositoryclaude-code-zero
Skill namereport-manager
Stars
53
Forks
4
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Report Manager 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/LeeJuOh/claude-code-zero/tree/main/plugins/vision-powers/skills/report-manager
  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/LeeJuOh/claude-code-zero.git /tmp/claude-code-zero
mkdir -p .claude/skills
cp -r /tmp/claude-code-zero/plugins/vision-powers/skills/report-manager .claude/skills/report-manager
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Report Manager 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 Report Manager 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 Report Manager 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.

Report Manager

Manage vision-powers reports — every persisted output (.html, .artifact.html, .md, .artifact.md): list, open, delete, search, and refine sections.

Paths

ResourcePath
Reports directory${CLAUDE_PLUGIN_DATA}/reports/
Plugin scripts${CLAUDE_SKILL_DIR}/../../scripts/

Operation Detection

Determine the operation from $ARGUMENTS:

KeywordsOperation
list, show, reports, lslist
open, view, browseopen
delete, remove, clean, prunedelete
search, find, grepsearch
refine, fix, update, adjust, change sectionrefine

Default to list if ambiguous.

list

Single call — returns structured JSON:

node ${CLAUDE_SKILL_DIR}/../../scripts/list-reports.js --data-dir "${CLAUDE_PLUGIN_DATA}"

Output contains reports_dir, count, and reports[] (each with index, filename, path, type, size, date, and artifact_url when a <report>.artifact.json sidecar exists).

Format as a numbered table with clickable links. Add an Artifact column only when at least one report in the list has artifact_url (omit the column entirely otherwise — most reports won't have one):

| # | Report | Type | Size | Date | Artifact |
|---|--------|------|------|------|----------|
| 1 | [filename](file:///absolute/path) | type | size | date | [Open](artifact_url) |
| 2 | [filename](file:///absolute/path) | type | size | date | — |

open

  1. No argument: open the most recent report
  2. Number: Nth from list output
  3. Partial name: glob match ${CLAUDE_PLUGIN_DATA}/reports/*{arg}*.{html,md}
bash
open <resolved-absolute-path>

Print the file:/// URL for reference. If the resolved report's list-reports.js entry has artifact_url, also print that as "Shared link: ".

delete

Always confirm with AskUserQuestion before deleting.

Filters:

  • Specific file: filename or number from list
  • Type: --type diff-visual
  • Age: --before 30d
  • All: --all

Steps:

  1. Resolve matching files (use list-reports.js output or ls)
  2. Show files that will be deleted (filename, size, date)
  3. Confirm via AskUserQuestion — "Delete N files" / "Cancel"
  4. rm each file on confirmation, and its <file>.artifact.json sidecar if one exists — an orphaned sidecar would make a future list claim a shared link for a report that's gone
  5. Report count deleted

search

  1. Filename: Glob ${CLAUDE_PLUGIN_DATA}/reports/*{query}*.{html,md}
  2. Content: Grep inside the reports for the query — in HTML focus on <title>, <h1>–<h3>, and text nodes; in markdown, headings and body text
  3. Display results with clickable file:// links

refine

Surgically edit a section of an existing report without full regeneration.

Why: Full regeneration re-rolls fonts, colors, and all content. Targeted edits preserve what works.

  1. Resolve target report: filename, number, partial name, or most recent if none given. Check for a sidecar: <report-path>.artifact.json — its presence means this file is an Artifact-channel file published to claude.ai (an .artifact.html fragment or an .artifact.md), not a plain local report. This changes steps 5–7 below.
  2. Identify section: If the user's message names specific sections, use those; otherwise Read the report, list <section id="..."> headings, and use AskUserQuestion to let the user pick
  3. Gather context: If the requested change references source code or git data, use Grep/Read to get correct info
  4. Apply edit: Read the target section, use Edit to modify it. Preserve HTML structure, CSS classes, and Mermaid/Chart.js formatting. Do not touch other sections.
    • When you re-author the section's content (not just patch a value), don't reintroduce behavioral slop. Read ${CLAUDE_SKILL_DIR}/../../references/design-system/anti-slop-tells.md for the named defaults to break.
  5. Validate:
    node ${CLAUDE_SKILL_DIR}/../../scripts/artifact-gate.js <report-path> [--content-only]
    Pass --content-only when step 1 found a sidecar (or the filename ends in .artifact.html) — design-layer checks (density, palette, font fallback, Mermaid classDef) don't apply to a page whose design is owned by the built-in artifact-design skill. If violations found, fix inline and re-validate (max 2 retries). Markdown reports (.md / .artifact.md) skip this script entirely — artifact-gate.js parses HTML only and would false-flag markdown's own ##/** syntax as leakage. Give the edited markdown the generating skills' hand-check instead: no leftover {{ }}/[STUB]/lorem placeholder tokens, and every link resolves.
  6. Visual self-audit (local HTML reports only): skip it for markdown reports and for Artifact-channel fragments — a local render of a fragment lacks the wrapper claude.ai adds, and artifact-design owns their look. For local HTML reports, follow ${CLAUDE_SKILL_DIR}/../../references/design-system/visual-self-audit.md on the edited section, rendering with:
    node ${CLAUDE_SKILL_DIR}/../../scripts/render-report.js <report-path> --data-dir "${CLAUDE_PLUGIN_DATA}"
  7. Republish (Artifact-channel files only — .artifact.html / .artifact.md): skip this step for local reports — nothing to publish. If step 1 found a sidecar, read it for url and title, then call the Artifact tool with file_path=<report-path>, url=<sidecar url>, and a description — passing url is what stacks the edit onto the same claude.ai link instead of minting a new one; a fresh session has no other way to target an existing artifact (this is exactly the gap a missing url arg leaves open). After a successful publish, rewrite the sidecar (node ${CLAUDE_SKILL_DIR}/../../scripts/write-artifact-sidecar.js --report <report-path> --url <url> --title <title>) so published_at reflects this refine.
    • No sidecar, but the filename still ends in .artifact.html or .artifact.md: this file was never successfully published (an earlier attempt fell back to local-only). Publish fresh — omit url — and write the sidecar for the first time.
    • Sidecar present but the republish call errors (the link died, e.g. the artifact was deleted upstream): publish fresh — omit url — write a new sidecar over the old one, and tell the user in one line: "New shared link published — any previously shared link now points to a stale version." Don't guess at why the old link died.
  8. Report: Print the file:// URL (local reports) or the claude.ai URL (Artifact-channel fragments), summarize what changed

Gotchas

  • Report type detection is filename-based: *-diff-visual → diff-visual, *-doc-visual → doc-visual, *-report → plugin-visual.
  • A local report and its Artifact-channel fragment are two separate files (e.g. 2026-07-06-x-doc-visual.html vs 2026-07-06-x-doc-visual.artifact.html) with independently designed content — refining one never touches the other. A partial-name match in step 1 of refine can hit both; if the resolved list has more than one candidate, ask which one rather than guessing.

Frequently asked questions

What does the Report Manager AI skill do?

Manage and refine vision-powers reports: list, open, delete, search, and refine sections. Use when asked to list, open, delete, search, or update generated HTML reports.

Why use Report Manager on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeeJuOh/claude-code-zero/tree/main/plugins/vision-powers/skills/report-manager. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Report Manager?

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 Report Manager?

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

Is the Report Manager AI skill free?

Yes. It is published on GitHub by LeeJuOh 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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