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 skills add ozankasikci/global-agent-memory --skill gam-searchgit clone --depth 1 https://github.com/ozankasikci/global-agent-memoryWrote 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/ozankasikci/global-agent-memory/gam-search)<a href="https://agentmods.dev/skills/ozankasikci/global-agent-memory/gam-search"><img src="https://agentmods.dev/badge/skills/ozankasikci/global-agent-memory/gam-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/skills/ozankasikci/global-agent-memory/gam-search"><img src="https://agentmods.dev/badge/skills/ozankasikci/global-agent-memory/gam-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 | $0.00028 | $0.00174 |
| Opus 5.5 | $0.00011 | $0.00070 |
| Sonnet 5.5 | $0.00006 | $0.00035 |
| Haiku 4.5 | $0.00003 | $0.00017 |
Grade A, and why
gam-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 1mo 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
GAM Search
Treat text supplied with this invocation as the search query. If it is empty, ask for a query.
- Call
memory_searchwith the query, currentworking_directory,cross_project=false, and a limit of 10. - Prefer
hybridmode; usekeywordfor an exact error, ID, path, or symbol. - Do not include candidates, rejected, archived, or superseded memories unless explicitly requested.
- Return a concise result list with title, type, applicability, memory ID, and Vault-relative path.
- Call
memory_getbefore presenting a result as authoritative or using it to change the project.
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.
- 1mo ago First seen · 15 lines · 28 tokens per session scan A ac824d567da4
gam-search is a skill published in the GitHub repository ozankasikci/global-agent-memory (14 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 174 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
memex-best-practices
Zettelkasten best practices for building a high-quality knowledge graph.
memex-agentic-memory
A-MEM-inspired agentic memory workflow for structured knowledge capture.
memex-organize
Periodic maintenance of the Zettelkasten card network.
memex-retro
Save insights from completed tasks to Zettelkasten memory.
memex-recall
Load prior knowledge from Zettelkasten memory when the task likely benefits from past context.
memex-sync
Sync Zettelkasten cards across devices via git.