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 tonyghiani/ai-essentials --skill memory-distillgit clone --depth 1 https://github.com/tonyghiani/ai-essentialsWrote 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/tonyghiani/ai-essentials/memory-distill)<a href="https://agentmods.dev/skills/tonyghiani/ai-essentials/memory-distill"><img src="https://agentmods.dev/badge/skills/tonyghiani/ai-essentials/memory-distill.svg" alt="Measured on agentmods" 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 | $0.00088 | $0.00833 |
| Opus 5 | $0.00044 | $0.00417 |
| Sonnet 5 | $0.00018 | $0.00167 |
| Haiku 4.5 | $0.00009 | $0.00083 |
Grade B, and why
memory-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 7d 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.
cat ~/.claude/memory-signal.jsonl How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory distill
The log-correction-signal hook captures every prompt where Marco corrected behaviour or stated a preference, at zero token cost. This skill turns that raw log into memory files. Run it periodically, not every session.
Why it works this way
Auto-extracting memories at the end of every session burns tokens and produces low-grade noise ("user wanted the button blue"). Corrections are the high-signal moments: they mark where the assistant's default diverged from what Marco actually wants. Logging is free; distilling is deliberate.
Workflow
Step 1 — Read the log
wc -l ~/.claude/memory-signal.jsonl 2>/dev/null || echo "no signal log yet"
cat ~/.claude/memory-signal.jsonl
Each line is { at, cwd, session, prompt, hits }. If the file is missing or empty, say so and stop; don't invent memories.
Step 2 — Read what's already stored
Memory lives per-project at ~/.claude/projects/<slug>/memory/. Read the relevant MEMORY.md index and any file that might already cover a theme. You are updating, not appending duplicates.
Step 3 — Group into themes
Cluster the raw prompts. A theme needs at least two independent occurrences, or one very explicit standing instruction ("from now on…"). Discard:
- One-off task corrections with no general rule ("no, the other file")
- Anything already covered by
CLAUDE.md, a skill, or the repo's own docs - Preferences derivable from the code itself (the
marco-code-styleskill covers style; don't duplicate it here)
For each surviving theme, write down the why. A memory without a reason gets misapplied later.
Step 4 — Propose, don't write
Present each candidate as:
### <slug>
**Type:** feedback | project | user | reference
**Claim:** <one line>
**Why:** <the reason it matters>
**Evidence:** <2-3 quoted fragments from the log, with dates>
**Action:** new file | update <existing-file.md> | supersedes <old-file.md>
Then ask which to keep, using a numbered list so a numbered reply maps by index.
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.
- 7d ago First seen · 91 lines · 88 tokens per session scan B bf0abbbbc569
memory-distill is a skill published in the GitHub repository tonyghiani/ai-essentials (6 stars, last pushed 29d ago), licensed MIT. It adds 88 tokens to every session and 833 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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