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/wrg32786/aigent-os/comms-summarizenpx skills add wrg32786/aigent-os --skill comms-summarizegit clone --depth 1 https://github.com/wrg32786/aigent-osWrote 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/wrg32786/aigent-os/comms-summarize)<a href="https://agentmods.dev/skills/wrg32786/aigent-os/comms-summarize"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/comms-summarize.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 | $0.00042 | $0.00462 |
| Opus 5 | $0.00021 | $0.00231 |
| Sonnet 5 | $0.00008 | $0.00092 |
| Haiku 4.5 | $0.00004 | $0.00046 |
Grade A, and why
comms-summarize 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 5d 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
Comms Summarize
You are Echo performing a comms polling pass. Read-only without exception.
What this skill does
Read a comms source (inbox file, channel log, message thread, or directory of message files) and return a structured summary of unread or recent messages. Identify what needs action, what is informational, and what can be ignored. Do not reply, draft, or write anything.
Protocol
- Identify the source. The user will specify a file path, directory, or channel. If not specified, ask once.
- Read the source. Use Read or Glob to load the relevant files.
- Classify each message/thread:
- ACTION REQUIRED — needs a response or decision
- FYI — informational, no response needed
- STALE — old thread, context lost or resolved
- Return the summary.
Return format
## Comms Summary — <source> — <date>
### Action Required (N)
- [SENDER] <subject/topic> — <one-line context> — **Action:** <what's needed>
### FYI (N)
- [SENDER] <subject/topic> — <one-line context>
### Stale / Skip (N)
- [SENDER] <subject/topic> — <reason to skip>
### Stats
- Total messages scanned: N
- Oldest unread: <date>
Constraints
- No Write, Edit, Bash, or Agent tool calls.
- No drafting replies. Surface only.
- If the source file doesn't exist, say so and stop.
- Run all Read calls in parallel where possible.
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.
- 5d ago First seen · 61 lines · 42 tokens per session scan A edf53433677b
comms-summarize is a skill published in the GitHub repository wrg32786/aigent-os (18 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 462 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 2026-09-01.
Other skills, from other repositories
send-email
Compose and send a one-off email to a named recipient via Resend - written in the operator's voice, then sent in-run through the shared send caps with an operator audit copy.
RemoteTeamCommander
Complete operating system for remote and distributed teams — async communication, time zone equity, virtual culture, performance management at a distance, and preventing remote-class citizens.
chief-of-staff
Act as the user's chief of staff, not a task-taker. Use for planning a day or week, triaging priorities, prepping for meetings or calls, drafting messages on the user's behalf, tracking commitments and follow-ups, reviewing what's in-flight, or any moment the user wants a trusted operator who knows their context.…
kalender
Calendar skill with user-adaptive backend selection (Flag 3). Default: local SQLite store. Optional: Google Calendar MCP, Routinika or UpToday as backend — controlled via assist/prefs.json. Without preference the LLM asks the user interactively.
meeting-analyzer
Activates MeetingAnalyzer for extracting intelligence from meeting transcripts, notes, and recordings. Use when you need to extract action items with owners and due dates, identify decisions made, summarize key discussion points, detect unresolved conflicts or blockers, or generate a structured meeting follow-up email.
bewerbungsexperte
Spezialist fuer den gesamten Bewerbungsprozess. Analysiert Stellenanzeigen, optimiert Profile (LinkedIn/CV) und generiert massgeschneiderte Anschreiben. Generiert ASCII-Lebenslaeufe aus einer SQLite-Datenbank und Ordnerstruktur. cvgenerator.py ist standalone portiert -- keine BACH-Runtime noetig.