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 HybridAIOne/hybridclaw --skill channel-catchupgit clone --depth 1 https://github.com/HybridAIOne/hybridclawWrote 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/hybridaione/hybridclaw/channel-catchup)<a href="https://agentmods.dev/skills/hybridaione/hybridclaw/channel-catchup"><img src="https://agentmods.dev/badge/skills/hybridaione/hybridclaw/channel-catchup/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/hybridaione/hybridclaw/channel-catchup"><img src="https://agentmods.dev/badge/skills/hybridaione/hybridclaw/channel-catchup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00026 | $0.01298 |
| Opus 5 | $0.00013 | $0.00649 |
| Sonnet 5 | $0.00005 | $0.00260 |
| Haiku 4.5 | $0.00003 | $0.00130 |
Grade A, and why
channel-catchup 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 12d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Channel Catchup
Creating a concise catch-up or summary of channel content.
Examples:
- "Summarize the last 50 messages from
#announcementsand#engineering." - "Give me the important posts from our HybridAI Discord server today."
- "Catch me up on this email thread."
- "Summarize what happened in the current TUI session."
Default To Action
Do not reflexively ask for scope if you can already do a useful catch-up from available context and tools.
Default to the broadest safe scope you can actually resolve:
- If channels are explicit, use them.
- If the platform/thread is explicit and no count is given, use sensible defaults.
- If the request is broad but concrete targets are already visible in context or tool output, read them and summarize.
- Only ask a clarification when no concrete readable target can be resolved without guessing.
When a reasonable assumption is needed, make it, do the catch-up, and state the assumption after the summary instead of blocking first.
Default limits when the user did not specify them:
- Discord: last 50 messages per resolved channel
- Email: last 20 messages from the current or explicit ingested thread
- If no timeframe is provided, summarize the most recent activity visible in those reads
Scope Resolution
Resolve scope aggressively instead of asking for it.
Use these defaults:
- if the platform is clear, proceed on that platform
- if the target set is broad, use all concrete readable targets you can already resolve
- if no timeframe is given, prefer the latest visible activity
- if no count is given, use the default limits above
Only ask a clarification when you cannot identify any concrete readable target without guessing. If you had to infer scope, note the assumption after the answer in one short line and keep moving.
Channel-Specific Workflow
Discord
- Use
messagewithaction="read"for each target channel before summarizing. - Prefer explicit channel IDs. If the user gives
#channel-name, includeguildId. - Read each channel separately, then merge findings into one summary.
- Do not say you need pasted messages if you can read the requested Discord channels directly.
- If the user names a Discord server but not channels, default to all concrete readable channels you can already resolve from context, tool descriptions, prior tool output, or the current server context.
- If the ask is broad and you can resolve multiple channels, prefer covering more channels over asking for narrower scope.
- If channels are explicit but timeframe is missing, read the recent bounded sample and summarize it as the latest activity instead of blocking on timeframe selection.
- Ask only if you still cannot identify any concrete readable channels without guessing.
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.
- 12d ago First seen · 142 lines · 26 tokens per session scan A fd8107f372db
channel-catchup is a skill published in the GitHub repository HybridAIOne/hybridclaw (132 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 1,298 once invoked, about $0.0001 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 2026-08-30.
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