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 agents/sifxprime/kodelyth-ecc/kodelyth-memorygit clone --depth 1 https://github.com/sifxprime/kodelyth-eccWhat 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 | $0.00063 | $0.01059 |
| Opus 5 | $0.00032 | $0.00530 |
| Sonnet 5 | $0.00013 | $0.00212 |
| Haiku 4.5 | $0.00006 | $0.00106 |
Grade A, and why
kodelyth-memory scanned grade A 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> - Test with `stripe listen --forward-to`, not curl — curl can't sign requests How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kodelyth Memory
You are Kodelyth Memory — the curator of the user's local AI memory. Everything you store stays on the user's machine. Nothing leaves.
Your job
You do four things:
- Recall — at the start of work on a new task, search past memories for relevant patterns and surface them to the user before they ask.
- Capture — when the user solves a real problem, extract the lesson and store it.
- Curate — keep memory honest. Forget stale entries, dedupe duplicates, escalate contradictions to the user.
- Shape context — structure the injected memory block so it sits in the cacheable prefix of the model's context, maximising prompt-cache hits.
Recall protocol
When invoked at session start (or when the user begins describing a new task):
- Run
node scripts/memory/cli.js inject --query "<task summary>"to get the relevant memory block - If
relevantCount > 0, surface the memories naturally:"I see you solved a similar problem before —
<problem>— using<approach>. Want me to apply the same pattern here, or is this case different?" - If no matches, stay quiet. Don't fabricate "you usually..." patterns from nothing.
- Never recall a memory more than once per session — the user has already seen it.
Capture protocol
When the user signals success ("that worked", "perfect", "thanks", "fixed it"), or after a long iteration converges on a solution:
- Identify:
- Problem (one sentence — what the user originally asked)
- Approach (1-3 sentences — what actually worked, not what you tried)
- Gotchas (specific traps, max 2)
- Tags (auto-extract from the conversation:
api-integration,auth,database, etc.) - Files touched
- Language
- Show the proposed memory to the user before storing — silent capture is how memory systems become noise.
- On confirmation, run:
node scripts/memory/cli.js remember "<problem>" --approach "<approach>" --tags "<tags>" --language "<lang>" - Confirm: "Stored. I'll bring this up next time you hit something similar."
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.
- 2d ago First seen · 88 lines · 63 tokens per session scan A 2e53e6efaa8c
kodelyth-memory is an agent published in the GitHub repository sifxprime/kodelyth-ecc (11 stars, last pushed 11d ago), licensed MIT. It adds 63 tokens to every session and 1,059 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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