Add Anydoc logo

Add Anydoc

OrganizationPopular
nanocoai
add-anydoc

Add local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when agents need to read attached Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, or text-based PDF files without uploading them to a hosted parser.

Overview

Publishernanocoai
Repositorynanoclaw
Skill nameadd-anydoc
Stars
30.9K
Forks
12.8K
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Add Anydoc 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/nanocoai/nanoclaw/tree/main/.claude/skills/add-anydoc
  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/nanocoai/nanoclaw.git /tmp/nanoclaw
mkdir -p .claude/skills
cp -r /tmp/nanoclaw/.claude/skills/add-anydoc .claude/skills/add-anydoc
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Add Anydoc 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 Add Anydoc 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 Add Anydoc 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.

Add AnyDoc

Install one pinned CLI and one focused container skill. Keep document conversion inside the agent container; do not change NanoClaw's attachment pipeline or add credentials, an MCP server, or a hosted parser.

Preflight

  1. Read CONTRIBUTING.md, docs/skill-guidelines.md, and the supply-chain section of docs/SECURITY.md.

  2. Run this check against the official npm registry before changing files:

    bash
    curl -fsSL "https://registry.npmjs.org/@firecrawl%2Fanydoc" | node -e '
      let body = "";
      process.stdin.setEncoding("utf8");
      process.stdin.on("data", (chunk) => (body += chunk));
      process.stdin.on("end", () => {
        const metadata = JSON.parse(body);
        const version = "0.1.6";
        const release = metadata.versions?.[version];
        const publishedAt = Date.parse(metadata.time?.[version] ?? "");
        const eligibleAt = publishedAt + 72 * 60 * 60 * 1000;
        if (!release) throw new Error(`${version} is missing from the registry`);
        if (release.deprecated) throw new Error(`${version} is deprecated: ${release.deprecated}`);
        if (!Number.isFinite(publishedAt)) throw new Error(`missing publish time for ${version}`);
        if (Date.now() < eligibleAt) throw new Error(`${version} is gated until ${new Date(eligibleAt).toISOString()}`);
        console.log(`${version} passed the 72-hour release gate`);
      });
    '

    Stop on any failure. Do not install a PR commit, add a minimumReleaseAgeExclude, enable lifecycle scripts, or silently substitute another version, unless the user explicitly approves it.

  3. Inspect container/cli-tools.json for @firecrawl/anydoc before changing files:

    • No entry: continue.
    • Exactly one entry at 0.1.6: leave it unchanged.
    • A duplicate or any other version: stop and report the conflict.
  4. Check whether container/skills/convert-documents-to-markdown/SKILL.md and src/anydoc-manifest.test.ts already exist. Reapplying this skill overwrites only those dedicated files.

  5. If data/v2.db exists, inspect per-group image pins before changing files. Standard derived images can be rebuilt from the updated shared image. Stop and report any other pin because its owner must decide how to rebuild it:

    bash
    if [ -f data/v2.db ]; then
      source setup/lib/install-slug.sh
      image_base="$(container_image_base)"
      foreign=0
      while IFS='|' read -r group_id image_tag package_count; do
        [ -z "$group_id" ] && continue
        if [ "$image_tag" != "${image_base}:${group_id}" ]; then
          echo "Foreign image pin: $group_id -> $image_tag" >&2
          foreign=1
        elif [ "$package_count" -eq 0 ]; then
          echo "Derived image cannot be rebuilt: $group_id has no configured packages" >&2
          foreign=1
        elif ! ncl groups get --id "$group_id" >/dev/null; then
          echo "Cannot reach NanoClaw through ncl for derived image: $group_id" >&2
          foreign=1
        fi
      done < <(pnpm exec tsx scripts/q.ts data/v2.db \
        "SELECT agent_group_id, image_tag, COALESCE(json_array_length(packages_apt), 0) + COALESCE(json_array_length(packages_npm), 0) FROM container_configs WHERE image_tag IS NOT NULL ORDER BY agent_group_id")
      [ "$foreign" -eq 0 ]
    fi

Install

Resolve this skill's bundled files from either Claude Code's skill variable or the project skill directory, then copy both files:

bash
project_root="$(git rev-parse --show-toplevel)"
skill_dir="${CLAUDE_SKILL_DIR:-$project_root/.claude/skills/add-anydoc}"
test -f "$skill_dir/container-skills/convert-documents-to-markdown/SKILL.md"
test -f "$skill_dir/anydoc-manifest.test.ts"
mkdir -p container/skills/convert-documents-to-markdown
cp "$skill_dir/container-skills/convert-documents-to-markdown/SKILL.md" \
  container/skills/convert-documents-to-markdown/SKILL.md
cp "$skill_dir/anydoc-manifest.test.ts" src/anydoc-manifest.test.ts

If the manifest has no AnyDoc entry, append this exact object to its JSON array. Do not add onlyBuilt; the package and its prebuilt Linux bindings have no install lifecycle script.

json
{ "name": "@firecrawl/anydoc", "version": "0.1.6" }

Validate and build

Run validation before building the image:

bash
pnpm exec vitest run src/anydoc-manifest.test.ts container/cli-tools.test.ts
pnpm run build
./container/build.sh

If pnpm rejects the package as too new, stop. Do not bypass the release-age policy.

Rebuild standard per-group images so groups with custom packages inherit the updated shared image:

bash
if [ -f data/v2.db ]; then
  source setup/lib/install-slug.sh
  image_base="$(container_image_base)"
  while IFS='|' read -r group_id image_tag; do
    [ -z "$group_id" ] && continue
    if [ "$image_tag" != "${image_base}:${group_id}" ]; then
      echo "Foreign image pin appeared during install: $group_id -> $image_tag" >&2
      exit 1
    fi
    ncl groups restart --id "$group_id" --rebuild
  done < <(pnpm exec tsx scripts/q.ts data/v2.db \
    "SELECT agent_group_id, image_tag FROM container_configs WHERE image_tag IS NOT NULL ORDER BY agent_group_id")
fi

Resolve this install's image name and exercise the native binding, not only the help path:

bash
source setup/lib/install-slug.sh
image="$(container_image_base):latest"
docker run --rm --entrypoint anydoc "$image" --version
printf 'name,count\nalpha,2\n' | \
  docker run --rm -i --entrypoint anydoc "$image" - --format csv | grep -q alpha
docker run --rm --entrypoint sh "$image" -c 'command -v timeout'

If timeout is absent, remove its wrapper from the installed container skill; do not add another dependency. Convert local DOCX, PPTX, and XLSX fixtures when available. Do not add private or large binary fixtures to the repository.

Restart

Restart this NanoClaw service only, so its running containers stop and default skills: "all" groups receive the new shared skill on their next spawn:

bash
source setup/lib/install-slug.sh
# macOS
launchctl kickstart -k "gui/$(id -u)/$(launchd_label)"
# Linux
systemctl --user restart "$(systemd_unit)"

Run only the command for the current platform. If NanoClaw is not service-managed, stop this install's running agent containers by their nanoclaw-install=<install-slug> label instead of matching every nanoclaw-v2 container on the host.

Smoke test

Use one real channel attachment and verify the complete path:

  1. Confirm the message supplies an absolute local path such as /workspace/inbox/<message-id>/<file>, and use that exact path.
  2. Convert it to /workspace/agent/converted/ and summarize only the relevant Markdown sections.
  3. Confirm an image-only PDF fails clearly and is not uploaded anywhere.
  4. For agents open to unknown senders, recommend an operator-set CONTAINER_MEMORY_LIMIT; AnyDoc's parser caps decompression, but NanoClaw containers have no memory limit by default.

Report that office documents now convert locally. Call out that scanned PDFs need OCR, embedded visuals may be incomplete, and spreadsheet Markdown is not authoritative for calculations.

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 Add Anydoc AI skill do?

Add local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when agents need to read attached Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, or text-based PDF files without uploading them to a hosted parser.

Why use Add Anydoc on TypingMind?

Because you install it once and use it with any model. Add Anydoc 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 Add Anydoc in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nanocoai/nanoclaw/tree/main/.claude/skills/add-anydoc. 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 Add Anydoc?

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 Add Anydoc?

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

Is the Add Anydoc AI skill free?

Yes. It is published on GitHub by nanocoai 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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