Rehydrate

Community

glebis

rehydrate

Put the real values back into an analysis that was produced from GREEN (placeholder) text — LOCALLY, using the user's own reversible map. Completes the confide round-trip (redact -> cloud-analyze the green -> rehydrate locally). Use when the user says "rehydrate", "restore real names", "unmask the analysis", "put the names back", "de-redact this output", "reverse the placeholders", or hands you an analysis full of [CONFIDE_PERSON_0001]/[CONFIDE_DATE_0002] plus a *.map.json. Runs only on the user's own map; the map never leaves the machine; nothing fetched or transmitted. Prints counts only — never echoes restored PII. Warns on placeholders not in the map (possible LLM hallucination).

Overview

Publisher	glebis
Repository	`claude-skills`
Skill name	`rehydrate`
Stars	379
Forks	56
Bundled files	1
License	MIT
Links	Skill source Repository

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by glebis on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/glebis/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/confide/skills/rehydrate .claude/skills/rehydrate

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rehydrate 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 Rehydrate 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 Rehydrate 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.

confide:rehydrate — restore real values into a placeholder analysis

This is the last step of the CONFIDE round-trip:

Redact locally with confide:anon (default reversible mode) → a GREEN copy with unique reserved-sentinel placeholders ([CONFIDE_PERSON_0001], [CONFIDE_EMAIL_0001], [CONFIDE_DATE_0002]…) plus a secret <name>.map.json (structured: green_sha256, entries[]…) that stays on the machine.
Analyze the GREEN text anywhere — including a cloud LLM. The analysis comes back full of those same placeholders (sometimes mangled to CONFIDE_PERSON_0001, [CONFIDE PERSON 0001]… — but always keeping the full CONFIDE_TYPE_NNNN core).
Rehydrate here: replace every placeholder with its original value from your own map, producing the real analysis — without the cloud ever seeing the originals.

Privacy invariants (do not violate)

Local-only, on the user's OWN map. The map never leaves the machine. This skill never fetches or transmits anything.
Counts only on stdout. The summary reports restored N, unmatched M. The restored text (which contains originals) is written to a local file; it is NEVER echoed to stdout beyond the counts.
Unmatched = possible hallucination. A placeholder that is not in the map is reported as unmatched and left in place — we never invent a value for it. Warn the user that these may be LLM hallucinations.
The <name>.restored.md output contains originals: it is local-only, do not share or commit it.

Run it

bash
python3 skills/rehydrate/scripts/rehydrate.py ANALYSIS_FILE [--map <name>.map.json]

ANALYSIS_FILE — the text/analysis containing placeholders.
--map <name>.map.json — the secret map from confide:anon. If omitted, the sibling *.map.json is auto-found (e.g. an analysis next to session.map.json, or one derived from session.green.md).
--out PATH — output path (default: <name>.restored.md next to the input).
--verify-green <green_file> — check the map's green_sha256 against that GREEN file; warns loudly if they don't match (wrong map for this document).

Robust to LLM mangling that still keeps the full CONFIDE_TYPE_NNNN core: [CONFIDE_PERSON_0001], [CONFIDE PERSON 0001], CONFIDE_PERSON_0001, and confide_person_0001 all restore to the same map entry. Ordinary prose lacking the CONFIDE prefix (e.g. "Person 1", "patient 1", "section 2") is never touched, and 0001 never eats 0010. Rehydration is idempotent (re-running on restored text is a no-op). Accepts both the structured map schema and a legacy flat map.

After running

Report the restore summary (restored N, unmatched M) — never paste PII.
If unmatched > 0, flag the placeholders as possible hallucinations not in the map.
Remind the user the *.restored.md is local-only (it now contains originals).

Bundled files

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

scripts/rehydrate.py7 KB

Frequently asked questions

What does the Rehydrate AI skill do?

Why use Rehydrate on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/glebis/claude-skills/tree/main/confide/skills/rehydrate. 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 Rehydrate?

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 Rehydrate?

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

Is the Rehydrate AI skill free?

Yes. It is published on GitHub by glebis 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

confide:rehydrate — restore real values into a placeholder analysis

Privacy invariants (do not violate)

Run it

After running

Bundled files

Frequently asked questions

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