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Gdrive Synthesize

OrganizationPopular
Kaelio
gdrive_synthesize

Synthesize durable KTX wiki pages from staged Google Drive document pulls. Load when a WorkUnit contains Google Doc raw files from `docs/**`.

Overview

PublisherKaelio
Repositoryktx
Skill namegdrive_synthesize
Stars
1.6K
Forks
104
Bundled files
Instructions only
LicenseApache-2.0
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 Kaelio on GitHub. Read the source before you install it.

Installation

Install the Gdrive Synthesize 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.
  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/Kaelio/ktx.git /tmp/ktx
mkdir -p .claude/skills
cp -r /tmp/ktx/packages/cli/src/skills/gdrive_synthesize .claude/skills/gdrive_synthesize
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gdrive Synthesize 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 Gdrive Synthesize 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 Gdrive Synthesize 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.

Google Drive Doc Synthesis

Use this skill when a WorkUnit contains staged Google Drive content from docs/**.

Role

Each WorkUnit is one Google Doc plus its metadata. Read the assigned raw files, then write a small set of durable wiki entries that capture reusable organizational knowledge. Write final memory directly; do not write candidates.

Required Workflow

  1. Read the WorkUnit notes and rawFiles list. Document content lives in page.md; metadata.json holds title, path, url, modified time, and Drive folder context.
  2. For each assigned doc, call read_raw_file, or read_raw_span for oversized docs when the notes specify a span.
  3. Search wiki_search for existing pages that overlap the WorkUnit topics. Prefer updating an existing page over creating a duplicate.
  4. Use context_evidence_search, context_evidence_read, and context_evidence_neighbors when indexed document chunks would help reconcile related facts. Pass chunkId and documentId values verbatim as returned by the evidence tools.
  5. Write durable business knowledge with wiki_write. Aim for a small number of high-quality pages per doc. Include rawPaths with the exact Google Drive raw files that support each page.
  6. If a doc references warehouse, dbt, Looker, Metabase, or MetricFlow objects, you may verify them with discover_data, entity_details, sql_execution, sl_discover, or sl_read_source, but Google Drive docs are knowledge-only in v1. Do not create semantic-layer sources under the gdrive connection.
  7. For every deleted raw path in the Eviction Set, call eviction_list, decide retention, then emit_eviction_decision. Do this even when no wiki write is needed.

What To Capture

Capture durable, reusable company knowledge:

  • policies, workflows, process rules, ownership conventions, and operating procedures
  • product definitions, business terminology, and organizational guidance
  • source-of-truth statements, caveats, conflict notes, and supersession guidance
  • cross-system aliases that connect doc terminology to warehouse, dbt, Looker, Metabase, or MetricFlow names

Skip noisy or transient content:

  • brainstorming notes with no durable rule
  • task lists, meeting scheduling details, and time-bounded status updates
  • duplicate docs with no new fact
  • shallow summaries that add no reusable policy or definition

Quality

Prefer fewer, stronger entries. Every wiki entry must cite at least one Google Doc using its title or path and last modified date when available. When evidence conflicts, write a conflict note inside the wiki page rather than choosing silently.

If one doc covers several related ideas, synthesize the shared durable rules instead of writing one thin page per paragraph. For oversized spans, read only the assigned span unless the WorkUnit explicitly asks for neighboring context.

Search existing wiki pages for the same tables: or sl_refs: frontmatter and for source-of-truth aliases before creating a new page. If an existing page already documents the same warehouse object or business concept, update it instead of creating a differently named duplicate.

Citation Style

md
## Agentic Harness
- The harness provides the operational framework that turns an agent prototype into a production system.
- Source: Google Doc - Herness, last modified 2026-05-24.
- Conflict note: An older internal note uses a narrower definition focused only on tool wiring; treat the current Google Doc as the durable operating definition unless replaced explicitly.

Semantic-Layer Rules

  • Google Drive docs are knowledge-only in v1; keep durable output in wiki pages.
  • Do not create semantic-layer sources under the gdrive connection.
  • If a doc references an existing warehouse or semantic-layer object and you can verify it, you may attach sl_refs in wiki output after confirmation.
  • If a doc mentions a table or source that cannot be verified, keep the identifier in wiki text as unverified or use emit_unmapped_fallback only when the missing physical object itself is the important durable fact.

Identifier Verification Protocol

Before writing a wiki page on any topic:

  1. discover_data({query: "<topic>"}) - see what wikis, SL sources, and raw tables already exist. Prefer updating existing pages over creating new ones.

Before emitting any schema.table or schema.table.column into a wiki body, tables: frontmatter, sl_refs, or emit_unmapped_fallback:

  1. entity_details({connectionId, targets: [{display: "<identifier>"}]}) - confirm the identifier resolves; inspect native types, FK/PK, and sampleValues.
  2. For literal values from the doc, such as status codes or plan tiers, check whether they appear in entity_details sampleValues for the relevant column. If sampleValues is short or the sample may have missed real values, run a sql_execution probe with the same warehouse connection id: sql_execution({connectionId, sql: "SELECT DISTINCT <col> FROM <ref> LIMIT 50"}).
  3. If the candidate identifier still does not resolve, do one of:
    • Use sql_execution({connectionId, sql: "SELECT 1 FROM <ref> LIMIT 0"}). If it errors, the identifier is fictional.
    • Wrap the identifier in [unverified - from <rawPath>] in the wiki body, citing the exact raw path that mentioned it.
    • When recording emit_unmapped_fallback with no_physical_table, include the failing probe error in clarification.
  4. Never copy <schema>.<table> placeholder strings from these instructions into output.

Tools

Allowed: read_raw_file, read_raw_span, wiki_search, wiki_read, wiki_write, discover_data, entity_details, sql_execution, sl_discover, sl_read_source, context_evidence_search, context_evidence_read, context_evidence_neighbors, emit_unmapped_fallback, eviction_list, emit_eviction_decision.

Not allowed: context_candidate_write, context_candidate_mark, sl_write_source, sl_edit_source, sl_validate.

Frequently asked questions

What does the Gdrive Synthesize AI skill do?

Synthesize durable KTX wiki pages from staged Google Drive document pulls. Load when a WorkUnit contains Google Doc raw files from `docs/**`.

Why use Gdrive Synthesize on TypingMind?

Because you install it once and use it with any model. Gdrive Synthesize 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 Gdrive Synthesize in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Kaelio/ktx/tree/main/packages/cli/src/skills/gdrive_synthesize. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gdrive Synthesize?

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 Gdrive Synthesize?

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

Is the Gdrive Synthesize AI skill free?

Yes. It is published on GitHub by Kaelio under the Apache-2.0 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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