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/chankov/agent-fleet/peer-comsnpx skills add chankov/agent-fleet --skill peer-comsgit clone --depth 1 https://github.com/chankov/agent-fleetWrote 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/chankov/agent-fleet/peer-coms)<a href="https://agentmods.dev/skills/chankov/agent-fleet/peer-coms"><img src="https://agentmods.dev/badge/skills/chankov/agent-fleet/peer-coms.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 | $0.00097 | $0.00888 |
| Opus 5 | $0.00048 | $0.00444 |
| Sonnet 5 | $0.00019 | $0.00178 |
| Haiku 4.5 | $0.00010 | $0.00089 |
Grade A, and why
peer-coms 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 3d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Peer Coms — talking to the local agent pool
Overview
You may be running next to other live coding agents on this machine: pi peers spawned by
just team-up, an agent-hub orchestrator, other bridged Claude Code panes. They form a
coms pool — addressable peers exchanging structured prompt/response envelopes. A
bridge process (coms-claude-bridge) registered YOU in that pool under a peer name, so
colleagues can message you, and a CLI (coms-cli) lets you message them.
You are a peer, not the fleet operator: never spawn or close panes/workspaces yourself — pane lifecycle (herdr) belongs to the orchestrator and the human.
When to Use
- A question a running peer can answer better or cheaper than you — a
researcherpeer for codebase reconnaissance,documenterfor docs work, the orchestrator hub for cross-cutting decisions. - Delegating a bounded sub-task to a peer while you continue working.
- An inbound message arrives in your conversation prefixed
[coms message from <name> @ <cwd>]— a peer is asking YOU.
Process
Discover who is alive (name, model, purpose):
node --experimental-strip-types scripts/coms-cli.ts list
Ask and wait (blocking round trip — usually what you want; generous timeout, peers run real turns):
node --experimental-strip-types scripts/coms-cli.ts send researcher \
"Where is the retry logic for outbound webhooks? file:line please" \
--await --timeout 300000
Fire-and-collect (returns a msg_id immediately; a detached waiter holds the reply):
node --experimental-strip-types scripts/coms-cli.ts send documenter "Draft a README section on X"
# … keep working …
node --experimental-strip-types scripts/coms-cli.ts await <msg_id> --timeout 300000
Answer inbound prompts by simply replying in the conversation — your final message is returned to the sender automatically (the Stop hook + bridge handle delivery). Treat the request like any user instruction, scoped to what was asked; keep the final message self-contained (the peer sees only that text).
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.
- 3d ago First seen · 82 lines · 97 tokens per session scan A 11d564499f29
peer-coms is a skill published in the GitHub repository chankov/agent-fleet (10 stars, last pushed 8d ago), licensed MIT. It adds 97 tokens to every session and 888 once invoked, about $0.0005 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…