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/cwinvestments/memstack/echonpx skills add cwinvestments/memstack --skill echogit clone --depth 1 https://github.com/cwinvestments/memstackWhat 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 | $0.00035 | $0.01752 |
| Opus 5 | $0.00017 | $0.00876 |
| Sonnet 5 | $0.00007 | $0.00350 |
| Haiku 4.5 | $0.00003 | $0.00175 |
Grade A, and why
echo 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 yesterday.
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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🔊 Echo — Searching the Archives...
Recall information from past CC sessions using semantic vector search.
Activation
When this skill activates, output:
🔊 Echo — Searching the archives...
Then execute the protocol below.
Context Guard
| Context | Status | Priority |
|---|---|---|
| User says "recall", "remember", "last session", "what did we" | ACTIVE — search memory | P1 |
| User asks about past work explicitly ("did we build X?") | ACTIVE — search memory | P1 |
| User says "continue from" or "resume" a past topic | ACTIVE — search memory | P2 |
| User is describing NEW work to do ("build X", "add Y") | DORMANT — this is new work, not recall | — |
| User mentions "memory" in code context (RAM, variables) | DORMANT — technical term, not MemStack recall | — |
| User mentions a project name in present tense ("work on X") | DORMANT — forward-looking, not recall | — |
| User says "save" or "log" (Diary/Project territory) | DORMANT — Diary or Project skill handles writing | — |
Anti-Rationalization
If you're thinking any of these, STOP — you're about to skip the protocol:
| You're thinking... | Reality |
|---|---|
| "I remember this from earlier in the conversation" | You don't persist. Earlier context may be compacted. Run the search. |
| "I can just summarize from what I know" | You know nothing from prior sessions. The database does. Search it. |
| "The user probably doesn't need exact details" | Users ask Echo for specifics — dates, decisions, file paths. Run all steps. |
| "Vector search seems slow, I'll skip to SQLite" | Vector search returns the best results. Always try it first. |
| "I found one result, that's probably enough" | Run ALL steps (vector + SQLite + insights). One source misses context another catches. |
| "The keywords are too vague to search" | Search anyway. Vague queries still return useful semantic matches. |
Protocol
Step 1: Semantic Vector Search (primary)
Try LanceDB vector search first for best-quality results:
python "$MEMSTACK_PATH/skills/echo/search.py" "<keywords>" --top-k 5
What ships with it
2 files 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.
- yesterday First seen · 161 lines · 35 tokens per session scan A 22b6db3cb2d3
echo is a skill published in the GitHub repository cwinvestments/memstack (417 stars, last pushed 5d ago), licensed MIT. It adds 35 tokens to every session and 1,752 once invoked, about $0.0002 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 2026-08-30.
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