Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add glebis/claude-skills --skill rehydrategit clone --depth 1 https://github.com/glebis/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/glebis/claude-skills/rehydrate)<a href="https://agentmods.dev/skills/glebis/claude-skills/rehydrate"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/rehydrate/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/glebis/claude-skills/rehydrate"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/rehydrate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00166 | $0.00947 |
| Opus 5 | $0.00083 | $0.00474 |
| Sonnet 5 | $0.00033 | $0.00189 |
| Haiku 4.5 | $0.00017 | $0.00095 |
Grade A, and why
rehydrate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 fullCONFIDE_TYPE_NNNNcore). - 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
unmatchedand left in place — we never invent a value for it. Warn the user that these may be LLM hallucinations. - The
<name>.restored.mdoutput contains originals: it is local-only, do not share or commit it.
Run it
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 fromconfide:anon. If omitted, the sibling*.map.jsonis auto-found (e.g. an analysis next tosession.map.json, or one derived fromsession.green.md).--out PATH— output path (default:<name>.restored.mdnext to the input).--verify-green <green_file>— check the map'sgreen_sha256against that GREEN file; warns loudly if they don't match (wrong map for this document).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 55 lines · 166 tokens per session scan A 4aec44de2949
rehydrate is a skill published in the GitHub repository glebis/claude-skills (374 stars, last pushed 8d ago), licensed MIT. It adds 166 tokens to every session and 947 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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