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/acn-ericlaw/agent-memory/hello-worldnpx skills add acn-ericlaw/agent-memory --skill hello-worldgit clone --depth 1 https://github.com/acn-ericlaw/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/acn-ericlaw/agent-memory/hello-world)<a href="https://agentmods.dev/skills/acn-ericlaw/agent-memory/hello-world"><img src="https://agentmods.dev/badge/skills/acn-ericlaw/agent-memory/hello-world.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.00665 |
| Opus 5 | $0.00023 | $0.00332 |
| Sonnet 5 | $0.00009 | $0.00133 |
| Haiku 4.5 | $0.00005 | $0.00067 |
Grade A, and why
hello-world 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
hello-world
The canonical demonstration skill. It proves the agent-memory portable skills layer works end-to-end, on any vendor. It deliberately does something tiny — the mechanism is the lesson, not the capability.
When to use
Run this when the user asks to test the skills layer, says "run hello-world", or wants a greeting that confirms skills are wired up.
What to do
- Run the bundled helper (preferred — it computes the timestamps). With an optional
name, run it and show its output:
It prints the greeting, the local time, a UTC timestamp, and a reminder that agent-memory records all session logs in UTC (persist-time). The script is agent-invoked — the tool itself runs no code (thesh agent-skills/hello-world/scripts/hello.sh "<name-or-omit>"no-build-step-agent-runinvariant); you run it at the user's direction. - No shell available? Print the greeting directly —
Hello from the agent-memory portable skills layer 👋— and still tell the user the current local time and UTC time, and that session logs are recorded in UTC. - Report the result — not your invocation path. Confirm the skill ran (show the greeting +
timestamps) and that you read the single neutral source
agent-skills/hello-world/SKILL.md— that is the demonstration: the portable layer works on this vendor. Do not try to report which path triggered you (native adapter vs.memory/PROTOCOL.mdbaseline). You can't tell reliably: a vendor like Gemini expands a/hello-worldslash command into this prompt before you see it, so the trigger is invisible to you, and the neutral skill reads identically on every path. The proof of native wiring is simply that the user's invocation ran this skill; how they invoked it (a/-command, a description match, or plain language) is theirs to know, not yours to guess. (Don't re-introduce path self-reporting — three cross-vendor dogfood runs showed agents get it wrong because the signal isn't available to them.)
What ships with it
1 file 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.
- 4d ago First seen · 50 lines · 45 tokens per session scan A d787434bf4b3
hello-world is a skill published in the GitHub repository acn-ericlaw/agent-memory (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 45 tokens to every session and 665 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 2026-08-31.
Other skills, from other repositories
Context Doctor
Identify and repair degradation in system prompt, external memory, and skills preventing you from following instructions or remembering information as well as you should.
memanto-companion
Inspect and manage the cross-session engineering memory that Memanto maintains for your Claude Code skills. Use when the user asks what Memanto remembers, wants to see their engineering profile, manually recall context for a skill, or store a decision. The automatic lifecycle hooks handle capture/injection on their…
memory-recall
Search and recall relevant memories from past sessions via memsearch. Use when the user's question could benefit from historical context, past decisions, debugging notes, previous conversations, or project knowledge -- especially questions like 'what did I decide about X', 'why did we do Y', or 'have I seen this…
ov-experience-memory
Retrieve and apply OpenViking Experience memories through the Agent runtime's generic OpenViking search and read tools. Use before or during executable, multi-step, or tool-based work such as coding, file or data changes, configuration, deployment, workflow execution, and failure recovery when prior operational…
mnemon
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
mnemon
Persistent memory for MiniMax Code. Recall durable context, store important facts and decisions, and link related memories with the mnemon CLI.