用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/lukemcqueen/hermes-cortex --skill agent-ergonomic-output命令会保持在同一行。复制前请横向滚动并检查完整内容。
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Cross-server agent health monitoring using binary status vectors — deploy health endpoints on each agent, poll from orchestrator, alert on state transitions.
Wire a self-hosted Langfuse instance to Hermes Agent — generate API keys, configure env vars, enable the bundled plugin, install SDK, and verify traces flow.
Use before enforcement code changes or shared-repo commits.
| name | agent-ergonomic-output |
| description | Use when building scripts whose stdout agents read (AXI). |
| version | 1.0.0 |
| category | software-development |
| platforms | ["linux","macos"] |
| aliases | ["axi","axi-conventions","toon-output","agent-facing-output"] |
| related_skills | ["cron-format-standard","architecture-review","requirements-elicitation","change-checklist","adversarial-verifier","cron-output-contracts"] |
Trigger on ANY of: creating or modifying a CLI script whose stdout an agent
consumes (fleet scripts, health checks, task lists, bus tooling); adding a
--toon mode; reviewing an output format; applying the AXI principles
(Agent eXperience Interface, by Kun Chen — MIT).
The core insight: the most expensive token cost is not a longer response — it is the follow-up call. Every convention below exists to eliminate one. Turns = LLM calls = the cost line.
| # | Principle | Rule |
|---|---|---|
| 1 | Token-efficient output | TOON-lite on stdout (name[N]{fields}: header + CSV rows), ~40% savings over JSON; JSON stays internal |
| 2 | Minimal default schemas | 3–4 fields per item (id, title, status); --fields escape hatch |
| 3 | Content truncation | Preview + ... (truncated, N chars total) + --full hint; never silently omit |
| 4 | Pre-computed aggregates | count: N of TOTAL; derived statuses like checks: 3/3 passed |
| 5 | Definitive empty states | "0 results with context", exit 0; never bare empty output |
| 6 | Structured errors & exit codes | Errors on stdout in data format; exit 0 (incl. no-op) / 1 error / 2 usage; idempotent mutations; no prompts; fail loud on unknown flags |
| 7 | Ambient context | Session-start dashboard (≤15 lines, PII-safe); session-end capture (metadata only) |
| 8 | Content first | No-args shows live state, not help text |
| 9 | Contextual disclosure | 1–3 complete next-step commands, placeholders, flags carried forward; omit when self-contained |
| 10 | Consistent help | Per-subcommand --help (flags+defaults+2–3 examples); fast bare --version from a leaf module |
Full detail + examples: references/axi-ten-principles.md.
Result:
verdict, [SILENT] empty state, cost footer). Only add totals/truncation
hints; never restructure it.count == len(rows), TOTAL from
the unfiltered query; contract test asserts it (verify-vs-original).--toon/--full flags beside existing output;
rollback is a per-script revert. Never big-bang a format change.python3 -c 'import ...' on the
deployed path) so a partial deploy fails at deploy time, not at cron
runtime.ops/scripts/lib/axi_out.py) with full contract tests + boundary
matrix (empty, 0, -1, None, non-ASCII, large N, oversized field) +
golden-parity fixtures.parse_known_args or ignored --fields
values produce plausible-looking wrong data — worse than an error. Fail
loud with the valid list + exit 2.--version is probed
constantly; keep the version constant in a leaf module (stdlib-only
imports) so the probe never loads the heavy command graph.<id> placeholders.Traceback, no absolute path, no
dependency-internal markers.references/axi-ten-principles.md — full distilled principles with TOON
examples + the Cortex status-quo table (which surfaces already conform).references/delegated-design-review.md — recipe for running elicit +
6-role party via delegated pro-model subagents when the user is absent.docs/axi-agent-ergonomics.md (principle distillation, committed).docs/elicit/2026-08-24_axi-implementation.md,
docs/design/2026-08-24-axi-implementation-decision.md (party: Option B —
shared axi_out.py layer — won 8.50 vs 4.25/5.75),
docs/plans/2026-08-24-axi-implementation.md (phased implementation).