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 agentmods add skills/haidrrrry/loop-engineering-skills/loop-memorynpx skills add haidrrrry/loop-engineering-skills --skill loop-memorygit clone --depth 1 https://github.com/haidrrrry/loop-engineering-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/haidrrrry/loop-engineering-skills/loop-memory)<a href="https://agentmods.dev/skills/haidrrrry/loop-engineering-skills/loop-memory"><img src="https://agentmods.dev/badge/skills/haidrrrry/loop-engineering-skills/loop-memory.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 | $0.00107 | $0.00729 |
| Opus 5 | $0.00053 | $0.00365 |
| Sonnet 5 | $0.00021 | $0.00146 |
| Haiku 4.5 | $0.00011 | $0.00073 |
Grade A, and why
loop-memory 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 3d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loop Memory
Reflexion-style verbal memory: the agent reflects on each attempt in writing, stores the reflection, and reads recent reflections before acting. Research (Shinn et al., 2023) shows this mechanism — reflect, store, re-read — beats blind retrying by wide margins (+22% on decision tasks over 12 trials, +11% on code) and beats memory-without-reflection by 8 points. The gain comes from written reasons, not from retrying harder.
The protocol
Before acting (every task)
- Read
.loop/LESSONS.md. - Apply the Standing rules section unconditionally.
- Read the 3 most recent entries. If any is relevant to the current task, state in one line how it changes your approach. If none is relevant, proceed — do not force it.
After acting (every attempt, pass or fail)
Append exactly one entry in the file's format:
## [date] — [task, 5 words max] — PASS|FAIL
- What happened: [one line]
- Root cause / why it worked: [one line]
- Next time: [one specific, checkable instruction]
Quality bar for "Next time":
- ❌ "Be more careful with the database" — not checkable
- ✅ "Run
npx prisma migrate deploybefore any seed script" — checkable - ❌ "Remember the API is tricky" — vague
- ✅ "The /users endpoint paginates at 50; always pass ?page= when counting"
Failure reflection, specifically
When an attempt failed, the reflection must answer: what did I believe that was wrong? Failed attempts usually come from a false assumption, not a typo. Name the assumption. That's the lesson.
Maintenance (when the file exceeds ~30 entries)
- Read all entries oldest-first.
- Any lesson that appears 2+ times graduates into Standing rules, rewritten as a single imperative line.
- Delete the oldest 20 entries after graduation.
- Never delete Standing rules without the user's approval.
What NOT to store
- Secrets, keys, tokens, personal data — never, even if they caused the failure.
- Narration ("I then tried X, after which Y…") — store conclusions only.
- Duplicate lessons — if it's already there, don't re-add; consider graduating it.
- Blame or self-criticism — lessons are instructions, not feelings.
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.
- 3d ago First seen · 70 lines · 107 tokens per session scan A 055a2d753c30
loop-memory is a skill published in the GitHub repository haidrrrry/loop-engineering-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 107 tokens to every session and 729 once invoked, about $0.0005 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.
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