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 sssstwee/tastedistill --skill tasted-distillgit clone --depth 1 https://github.com/sssstwee/tastedistillWrote 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/sssstwee/tastedistill/tasted-distill)<a href="https://agentmods.dev/skills/sssstwee/tastedistill/tasted-distill"><img src="https://agentmods.dev/badge/skills/sssstwee/tastedistill/tasted-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/sssstwee/tastedistill/tasted-distill"><img src="https://agentmods.dev/badge/skills/sssstwee/tastedistill/tasted-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 | $0.00076 | $0.02657 |
| Opus 5 | $0.00038 | $0.01328 |
| Sonnet 5 | $0.00015 | $0.00531 |
| Haiku 4.5 | $0.00008 | $0.00266 |
Grade B, and why
tasted-distill scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- `$HOME/.codex/config.toml` without copying secrets or volatile machine state This is a copy
97% identical to distill — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Distill: Improve The Next Run
Use this skill after meaningful work has produced a lesson.
Prefix your first response line with ⚗️ inline, not as its own paragraph.
Before the workflow, apply ../../shared-rules/host-compatibility.md, ../../shared-rules/portable-profile.md, and ../../shared-rules/personalization.md for explicit TasteD/TasteDistill invocations. If this skill is already running the Local Personalization Bootstrap, use those shared rules only as host-safety, idempotence, and destination policy.
Apply ../../shared-rules/runtime-hygiene.md when distillation reads logs, creates generated evidence, invokes helper scripts, or runs browser/runtime checks.
Apply ../../shared-rules/memory-protocol.md when the request involves cross-agent memory, host memory refresh, profile sync, or memory health checks.
Outcome Contract
- Outcome: current work improves future agent behavior through reusable guidance with scope, trigger, evidence, and destination.
- Done when: each lesson is classified as update now, keep candidate, or discard, and the chosen destination is the narrowest useful one.
- Evidence: user corrections, failed attempts, verified fixes, tests, command output, diffs, logs, delivery results, and stable project conventions.
Taste Distillation Loop
work -> evidence -> lesson -> durable rule -> better next run
Distillation is not a transcript summary. It turns repeated, verified behavior into future execution guidance. A lesson should explain when the agent should behave differently next time, what evidence supports the rule, and where the rule belongs.
Local Personalization Bootstrap
Use this mode when the user asks to initialize these skills from their existing Codex or compatible agent memory, conversation history, logs, or prior task outcomes.
Do not assume those sources are already loaded. Installing a skill does not automatically import a user's historical conversations or memories. Explicitly invoking the TasteD/TasteDistill plugin or any tasted-* skill should perform a one-time bootstrap check through ../../shared-rules/personalization.md. If no local TasteDistill profile exists, run this bootstrap before continuing with the requested skill.
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.
- 10d ago First seen · 175 lines · 76 tokens per session scan B 2c789c990ddd
tasted-distill is a skill published in the GitHub repository sssstwee/tastedistill (2 stars, last pushed 3mo ago), licensed MIT. It adds 76 tokens to every session and 2,657 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). It is 97% identical to distill, differing in 12 lines, and is treated as a copy.
Other skills, from other repositories
weekly-digests
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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.
hivemind-memory
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memory-audit-pattern-extraction
A method for investigating repeated mistakes by comparing related memories and checking whether an earlier reminder failed. It looks at where the reminder was stored, when it was created, and whether it was strong enough to prevent the mistake.
init
Install or update OwnMem in the current repository. Use when the user asks to set up OwnMem, add local project memory for coding agents, or refresh an existing OwnMem installation after a version bump.
mnemo-cortex
Installs and wires Mnemo Cortex (local-first persistent memory) into OpenClaw and other MCP-capable agents. Use for cross-session recall, decision history, or multi-agent shared memory.