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 grpcer/ownmem --skill ownmem-dashboardgit clone --depth 1 https://github.com/grpcer/ownmemWrote 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/grpcer/ownmem/ownmem-dashboard)<a href="https://agentmods.dev/skills/grpcer/ownmem/ownmem-dashboard"><img src="https://agentmods.dev/badge/skills/grpcer/ownmem/ownmem-dashboard.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 5.1 | $0.00055 | $0.00506 |
| Opus 5 | $0.00028 | $0.00253 |
| Sonnet 5 | $0.00011 | $0.00101 |
| Haiku 4.5 | $0.00006 | $0.00051 |
Grade A, and why
ownmem-dashboard 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.
This is a copy
97% identical to dashboard — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Open OwnMem Console
OwnMem Console renders this repository's memory metrics — adoption funnel, recall latency, corpus health, governance — in the browser. It binds 127.0.0.1 only; nothing is served off this machine.
If npx ownmem dashboard fails because the layer is missing, the repository
was initialized without it. Re-run init with --layers dashboard (see the
init skill), then retry.
Start it for the user
The server stays resident. Start it in the background; if an instance is
already running, the same command returns "reused": true instead of starting
a second one.
Do not redirect --json output to /tmp or any other shared directory.
That JSON contains a long-lived access token, and /tmp is commonly
world-readable.
In Claude Code, use the Bash tool with run_in_background: true. In other
hosts, start the process in the background without capturing the token to a
world-readable file:
npx ownmem dashboard --json
Then read the URL from the private instance record (mode 0600 under
.local-test/):
npx ownmem dashboard --status --json
Open the url field in the browser. Keep the #t= fragment — the access
token lives in the URL fragment and never reaches the server; without it the
page only shows an access notice.
The CLI defaults to a random port. Pass --port 45300 (or another free local
port) when the user needs a stable bookmark, and keep using that port later.
After opening, run npx ownmem report --since 7d once and give the user a
one-line summary: adoption north star, latency P50/P95, and the most notable
gap or warning. When the sample is small, say so instead of dressing process
metrics up as adoption.
Lifecycle
npx ownmem dashboard --status --json
npx ownmem dashboard --stop
npx ownmem dashboard --open
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 Changed · +10 lines 50d84fbec80f
- 8d ago First seen · 50 lines · 55 tokens per session scan A 42b7944cfa97
ownmem-dashboard is a skill published in the GitHub repository grpcer/ownmem (275 stars, last pushed 2d ago), licensed Apache-2.0. It adds 55 tokens to every session and 506 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to dashboard, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
ultramemory-snapshot
Compose and save a durable, wayback-grade session snapshot to UltraMemory. Use this whenever you are asked to write a session snapshot or rollup of the work just done — in particular when the UltraMemory capture hook nudges you to "Compose a session snapshot per the ultramemory-snapshot Skill rubric ... and save it…
setup
Guides Claude through first-time UltraMemory configuration after plugin install — API key, MCP server registration, test recall, and 401/403 troubleshooting.
ultramemory-recall-first
Load when the user asks about anything they may have told their AI before, wants persistent memory across tools, or asks what UltraMemory knows — recall from the user's connected UltraMemory connector first, write durable facts back, and never invent a memory.
krimto-write-fact
Use when the user asks you to remember something for later, save team knowledge, record a decision, or note a durable fact about the project, person, or team. Triggers on "remember that", "save this", "add to memory", "note for the team". Do not use for conversational context.
krimto-hierarchical-scope
Use when deciding what scope to store a fact at, or when reasoning about whether a fact applies to the current user. Krimto uses a user -> team -> org hierarchy with precedence rules. Triggers when scope selection is required.
krimto-recall-team
Use when starting a task, joining a conversation about a project, or before answering a question that needs team context. Triggers on "what do we know about X", "team's approach to Y", or before any domain-specific work.