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 instructions/mraza007/echovault/agents-mdgit clone --depth 1 https://github.com/mraza007/echovaultWhat 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 | $0.00411 | $0.00411 |
| Opus 5 | $0.00205 | $0.00205 |
| Sonnet 5 | $0.00082 | $0.00082 |
| Haiku 4.5 | $0.00041 | $0.00041 |
Grade A, and why
echovault AGENTS.md 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 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.
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.
What it actually says
Local Memory
You have access to a persistent memory system via the memory CLI. Use it to save important decisions, patterns, bugs, context, and learnings — and retrieve them in future sessions.
At Session Start
Check available memories for this project:
memory context --project
Then use memory search <query> to retrieve full details on any relevant memory.
Saving Memories
When you make a decision, fix a bug, discover a pattern, set up infrastructure, or learn something non-obvious:
memory save \
--title "Short descriptive title" \
--what "What happened or was decided" \
--why "Reasoning behind it" \
--impact "What changed as a result" \
--tags "tag1,tag2,tag3" \
--category "decision" \
--related-files "src/auth.ts,src/middleware.ts" \
--source "codex" \
--details "Context:
Options considered:
- Option A
- Option B
Decision:
Tradeoffs:
Follow-up:"
Categories: decision, pattern, bug, context, learning
Searching Memories
memory search "your query" # search all projects
memory search "your query" --project # current project only
memory search "your query" --source codex # from specific agent
Getting Full Details
When search results show "Details: available":
memory details <memory-id>
Rules
- Always capture thorough details — never omit reasoning or context
- Never include API keys, secrets, or credentials in any field
- Wrap sensitive values in
<redacted>tags if referencing them - Search before deciding — check if a decision was already made
- Save after doing — capture decisions, fixes, and learnings as you go
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 · 65 lines · 411 tokens per session scan A f77aa62a7734
echovault AGENTS.md is an instructions file published in the GitHub repository mraza007/echovault (148 stars, last pushed 1mo ago), licensed MIT. It adds 411 tokens to every session, about $0.0021 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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