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 Clamepending/videomemory --skill videomemory-channelgit clone --depth 1 https://github.com/Clamepending/videomemoryWrote 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/clamepending/videomemory/videomemory-channel)<a href="https://agentmods.dev/skills/clamepending/videomemory/videomemory-channel"><img src="https://agentmods.dev/badge/skills/clamepending/videomemory/videomemory-channel/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/clamepending/videomemory/videomemory-channel"><img src="https://agentmods.dev/badge/skills/clamepending/videomemory/videomemory-channel.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 | $0.00032 | $0.00551 |
| Opus 5.5 | $0.00013 | $0.00220 |
| Sonnet 5.5 | $0.00006 | $0.00110 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
videomemory-channel 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 2mo 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
VideoMemory Channel
VideoMemory events arrive as <channel source="videomemory" ...> messages.
When an event arrives:
- Treat the
note/ event body as a VideoMemory task update, not as arbitrary user chat. - Use
mcp__videomemory__inspect_taskif you need the current task state. - If the event says the trigger condition happened, complete the requested follow-up action.
- For a user-visible acknowledgement in channel tests, call
mcp__videomemory__reply. - Keep responses short. Do not start polling loops.
The channel server listens on localhost only by default:
- health:
GET http://127.0.0.1:8791/health - webhook:
POST http://127.0.0.1:8791/videomemory-event - replies/SSE:
GET http://127.0.0.1:8791/events
Use VIDEOMEMORY_CLAUDE_CHANNEL_TOKEN if the endpoint needs a bearer token.
When the user asks Claude to watch for something on camera:
- Call
mcp__videomemory__setup_localif the user asked to install, download, set up, or use VideoMemory and setup has not already been confirmed. - Use
mcp__videomemory__list_devicesto choose the targetio_id. - Use
mcp__videomemory__inspect_deviceif you need to verify camera/frame readiness before creating the monitor. - Use
mcp__videomemory__create_monitorwith only the visual condition intask_description. - For simple true/false conditions such as "a person is visible", "the phone is
visible", or "the door is open", set
monitor_typetobinaryso VideoMemory uses the local FastVLM done monitor. - Read the
readinessobject returned bycreate_monitor. Ifreadiness.readyis false, report the blocker instead of saying the monitor is fully armed. - Keep any user-facing follow-up action in your own response plan.
- Report the created task id and stop; VideoMemory owns the long-running watch.
If events are not arriving, call mcp__videomemory__configure_channel_webhook
and then retry a synthetic event from the host with videomemory claude test-event.
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.
- 2mo ago First seen · 46 lines · 32 tokens per session scan A 1e85f7753045
videomemory-channel is a skill published in the GitHub repository Clamepending/videomemory (5 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 551 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 2026-08-31.
videomemory-channel compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| videomemory-channelClamepending/videomemory | Skill | 5 | 5mo ago | MIT | A | 32 | Claude Code |
| gke-compute-classesgoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 83 | Claude Code, Codex |
| jetson-diagnosticNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 30 | Claude Code, Codex |
| holoscan-install-wheelNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 34 | Claude Code, Codex |
| offensive-z-waveSnailSploit/Claude-Red | Skill | 10k | 25d ago | MIT | A | 113 | Claude Code, Codex |
| doca-socket-relayNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 236 | Claude Code, Codex |
| hsb-flashNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | B | 94 | Claude Code |