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.
git clone --depth 1 https://github.com/studiomeyer-io/studiomeyer-marketplaceWrote 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/commands/studiomeyer-io/studiomeyer-marketplace/memory-search)<a href="https://agentmods.dev/commands/studiomeyer-io/studiomeyer-marketplace/memory-search"><img src="https://agentmods.dev/badge/commands/studiomeyer-io/studiomeyer-marketplace/memory-search/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/studiomeyer-io/studiomeyer-marketplace/memory-search"><img src="https://agentmods.dev/badge/commands/studiomeyer-io/studiomeyer-marketplace/memory-search.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00017 | $0.00238 |
| Opus 5 | $0.00009 | $0.00119 |
| Sonnet 5 | $0.00003 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
memory-search 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 10d 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
Search the user's StudioMeyer Memory for: $ARGUMENTS
- Call
nex_searchfrom thestudiomeyer-memoryMCP server withquery: "$ARGUMENTS"andlimit: 10. Letexpand: true(the default) handle synonym and temporal expansion. - If the query looks fuzzy or aggregation-heavy (contains words like "all", "how many", "summarize", "total"), also set
agentic: trueso the server does iterative retrieval with a completeness check. - Present the top 5 results as a short list:
- Type (learning / decision / entity / session / skill)
- One-line summary
- Date
- Confidence or relevance score if notable
- If none of the results feel relevant, tell the user directly and suggest rephrasing or broadening the query. Do not pad with weak matches.
Do not invent details not in the search result. Cite only what the server returned.
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.
- 10d ago First seen · 18 lines · 17 tokens per session scan A 2559123f22b9
memory-search is a command published in the GitHub repository studiomeyer-io/studiomeyer-marketplace (2 stars, last pushed 5d ago), licensed MIT. It adds 17 tokens to every session and 238 once invoked, about $0.0001 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.
Other commands, from other repositories
pane
Open the Engram graph pane — make sure the machine core is running and share the URL.
save
Manually save current context as a memo to the memex vault.
status
Show memex statistics and status including projects, memos, and pending items.
digest
Digest this project into Engram — an explicit, one-time ingestion of the current working tree into typed memory nodes.
log
Command "log" from allenc84/sapience, covering /log — judgment ledger command, routing, new assessment: /log, review: /log review [domain] and resolve: /log resolve.
recall
Search the engineering memlog and inject the top matching prior lessons. Use when you suspect a recurring issue.