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 CODE-SAURABH/OpenSkills --skill agent-memorygit clone --depth 1 https://github.com/CODE-SAURABH/OpenSkillsWrote 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/code-saurabh/openskills/agent-memory)<a href="https://agentmods.dev/skills/code-saurabh/openskills/agent-memory"><img src="https://agentmods.dev/badge/skills/code-saurabh/openskills/agent-memory/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/code-saurabh/openskills/agent-memory"><img src="https://agentmods.dev/badge/skills/code-saurabh/openskills/agent-memory.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 | $0.00071 | $0.07556 |
| Opus 5.5 | $0.00028 | $0.03022 |
| Sonnet 5.5 | $0.00014 | $0.01511 |
| Haiku 4.5 | $0.00007 | $0.00756 |
Grade C, and why
agent-memory scanned grade C 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 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.
Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
cp ~/Library/Application\ Support/Google/Chrome/Default/Cookies /tmp/chrome-cookies.db How it starts
The opening of the file, as written. The whole thing — 966 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Memory — Unified Skill
This skill unifies three complementary capabilities into a single, coherent workflow:
/learn— Session Memory Management — Persist, search, prune, and export what the agent has learned about your codebase and project across sessions./browse— Browser-Based QA Testing — Drive real Chromium (headless or headed), click elements, take screenshots, import cookies, and assert page state for production-grade QA./pair-agent— Multi-Agent Coordination — Spawn parallel sub-agents on isolated scopes, aggregate results, and hand off context cleanly between agents.
Part 1 — Memory Management (/learn)
1.1 Philosophy: Why Memory Matters
Every time the agent explores your codebase, it discovers implicit patterns that are expensive to rediscover:
- Which modules are load-bearing vs. experimental
- Naming conventions that are project-local (not language-default)
- Fragile integration points that have broken before
- Performance invariants the team cares about
- Domain-specific jargon used in comments and variable names
Without memory, the agent starts cold every session. With memory, compound knowledge accumulates — each session builds on prior sessions, reducing repeated archaeology and increasing the precision of every suggestion.
Principle: Memory is a first-class engineering artifact. Treat it like documentation.
1.2 Memory Scopes
There are two distinct scopes of memory. Always be explicit about which scope you are reading from or writing to.
Global Memory (~/.agent-memory/global/)
Stores patterns that apply across all projects on this machine:
- Preferred code style decisions (e.g., "always use early-return guards")
- Recurring architectural preferences (e.g., "prefer repository pattern over active record")
- User-level shortcuts and workflow preferences
- Learned tool behaviors (e.g., "this user's Makefile uses
make lintnotmake check")
Project Memory (<repo-root>/.agent-memory/)
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 · 966 lines · 71 tokens per session scan C 6731944fd229
agent-memory is a skill published in the GitHub repository CODE-SAURABH/OpenSkills (3 stars, last pushed 2mo ago), licensed MIT. It adds 71 tokens to every session and 7,556 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it C with 1 finding (reaches for credential files). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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