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 WinterDDo/claude-skill-flywheel --skill distillgit clone --depth 1 https://github.com/WinterDDo/claude-skill-flywheelWrote 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/winterddo/claude-skill-flywheel/distill)<a href="https://agentmods.dev/skills/winterddo/claude-skill-flywheel/distill"><img src="https://agentmods.dev/badge/skills/winterddo/claude-skill-flywheel/distill/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/winterddo/claude-skill-flywheel/distill"><img src="https://agentmods.dev/badge/skills/winterddo/claude-skill-flywheel/distill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00054 | $0.00350 |
| Opus 5 | $0.00027 | $0.00175 |
| Sonnet 5 | $0.00011 | $0.00070 |
| Haiku 4.5 | $0.00005 | $0.00035 |
Grade A, and why
distill 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 9d 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.
What it actually says
Distill the flywheel
Read ~/.claude/.flywheel/corrections.md and ~/.claude/.flywheel/principles.md.
For each recurring theme across the corrections, test it against the three promotion gates:
- Seen 3+ times in genuinely different situations (not the same task replayed).
- Holds across 3 domains (for example coding, writing, decisions) — not a one-off quirk.
- Deletion test: removing the principle would cause an observable regression.
For every theme that passes all three:
- Append a one-line principle to the In force section of
principles.md, using the format[date] | domains: [d1, d2] | the principle in one or two sentences. - Note which corrections it subsumes so they can be thinned from the log.
Then maintain the rest:
- Demote any in-force principle whose violations have recurred (it was stated wrong); remove it from In force so it stops re-entering sessions.
- Prune pool entries with no recurrence in 60 days.
Be ruthless: maturity is fewer principles, not more. If "In force" only ever grows, you are collecting scenarios instead of finding root causes.
Finish by reporting what you promoted, demoted, and pruned, and how many corrections remain unconsolidated.
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.
- 9d ago First seen · 26 lines · 54 tokens per session scan A 740150df7f16
distill is a skill published in the GitHub repository WinterDDo/claude-skill-flywheel (2 stars, last pushed 3mo ago), licensed MIT. It adds 54 tokens to every session and 350 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
weekly-digests
Generate a serial week-by-week narrative digest of a project's full claude-mem timeline. Splits the timeline into per-ISO-week files, then runs one consecutive subagent per week — each receiving the prior week's carry-forward block — to produce one chapter per ISO week of data. Use when asked for "weekly digests"…
mode-creator
Interactively create, install, activate, and verify custom claude-mem modes, including domain-specific observation types, concept tags, optional Telegram alerts, bot setup, worker restart, and startup-context verification. Use this whenever someone asks to customize what claude-mem remembers, create or change a mode…
cloud-sync
Set up or check claude-mem cloud sync with cmem.ai Pro. Use when the user says "set up cloud sync", "sync my memories", "cmem pro", "cloud backup", "sync status", or wants their memory database backed up or synced to their cmem.ai account.
knowledge-agent
Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.
claude-mem-install
Use this when setting up claude-mem on Cursor: local or remote worker, local host-login observer or remote cmem.ai inference.
how-it-works
Explain how claude-mem captures observations, when memory injection kicks in, and where data lives. Use when the user asks "how does claude-mem work?" or "what is this thing doing?".