Borrowing it
Nothing to install: this file belongs to agentculture/learn-cli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/agentculture/learn-cli/main/.claude/skills/communicate/SKILL.mdgit clone --depth 1 https://github.com/agentculture/learn-cliWrote 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/agentculture/learn-cli/communicate)<a href="https://agentmods.dev/skills/agentculture/learn-cli/communicate"><img src="https://agentmods.dev/badge/skills/agentculture/learn-cli/communicate/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/agentculture/learn-cli/communicate"><img src="https://agentmods.dev/badge/skills/agentculture/learn-cli/communicate.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 | $0.00184 | $0.03681 |
| Opus 5.5 | $0.00074 | $0.01472 |
| Sonnet 5.5 | $0.00037 | $0.00736 |
| Haiku 4.5 | $0.00018 | $0.00368 |
Grade A, and why
communicate 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.
This is a copy
97% identical to communicate — 8 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.
How it starts
The opening of the file, as written. The whole thing — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Communicate (Cross-Repo + Mesh)
Steward's job is alignment across the AgentCulture mesh; that surfaces in four distinct channels:
- Tracked, async hand-offs — a gap in another repo (a missing public
API, a divergent skill, a documentation ask) where an agent on the
other side needs to act, and the ask should outlive the conversation.
→
post-issue.sh(GitHub). - Follow-up on a tracked thread — a status update, an answer to a
question, or a "this is done" note on an issue that's already open.
→
post-comment.sh(GitHub). - Inbound state read — pulling current issue body + comments from a
sibling repo so a brief or plan can inline what's there instead of
saying "see issue #N." →
fetch-issues.sh(GitHub). - Ephemeral coordination — a status ping, a question, a "PR ready
for merge" notice on a Culture mesh channel where the audience is
already listening.
→
mesh-message.sh(Culture IRC).
All four live under one skill because they share the same audience (sibling-repo agents) and the same red flag (don't double-post the same ask across post + mesh — pick one).
Backed by agtag
The three GitHub verbs (post-issue.sh, post-comment.sh,
fetch-issues.sh) are thin wrappers around the agtag CLI
(agtag issue post|reply|fetch). agtag handles auto-signature
resolution from the local culture.yaml (falling back to repo
basename), JSON output mode, and a uniform exit-code policy. Read
agtag learn for the agent-facing self-teaching prompt and
agtag explain agtag / agtag explain issue for the surface docs —
this SKILL.md does not re-document agtag's flags.
mesh-message.sh stays a culture channel message wrapper for now;
agtag mesh transport is slated for v0.2.
When to Use
Issue mode (post-issue.sh)
- A gap surfaces in another repo's surface (missing public API, wire-format compat fix, divergent skill, documentation ask).
- You're handing off a self-contained brief to a sibling-repo agent.
- (steward-specific — supplier role.) You're onboarding a sibling to the
stack — "set it up", "align it", "update it with our stack", "set up the
pipelines". The deliverable is an issue with a self-contained brief, never
files written into that repo. In steward, quote steward's
docs/sibling-pattern.md(required artifacts) anddocs/skill-sources.md(the skill set to vendor) into the brief so it stands alone; steward'sCLAUDE.md"Steward's lane" section is the canonical statement. Downstream vendors of this skill don't onboard siblings — those steward-side docs don't exist in your repo, so skip this bullet. - You're asking a question that benefits from a tracked artifact rather than ephemeral chat.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 337 lines · 184 tokens per session scan A e90210d70403
communicate is a skill published in the GitHub repository agentculture/learn-cli (1 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 184 tokens to every session and 3,681 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to communicate, differing in 8 lines, and is treated as a copy.
Other skills, from other repositories
antfu-issue-triage
Triage open issues and PRs of the current GitHub repo - find already-fixed, duplicate, and spam items, suggest labels, gauge demand from reactions and comments, then present a table of proposed actions and comments for confirmation before touching anything. Use when asked to triage, organize, clean up, or groom issues…
mcore-split-pr
Split a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.
engineer-bot-ops
A workflow for carrying an engineering task from scope through implementation and reviewable delivery. It works with a repository's branch, existing changes, rules, checks, and permissions while separating completed, unverified, and next-step work.
shiplog
Recap of everything shipped since the last run - cross-repo PRs, security fixes, star deltas, and X traction, synthesized into a digest article and a ready-to-post shiplog in your voice.
llxprt-issue-workflow
Use this skill when asked to address, fix, or work on a GitHub issue in the llxprt-code repository. Covers the complete issue lifecycle - branch setup, gh CLI usage, test-first planning, subagent delegation and review loops, the full verification cycle (including the zai-glm-flash smoke test), open code review (ocr)…
connect
Choose which wiki this session uses, the team project's pages on the Nimbalyst server or the project's local wiki of files, and connect a repository to its team project. Use at the start of a task before any wiki tool, when a wiki tool returns reponotbound, ambiguousproject, pinmismatch, projectnotaccessible…