Aero
Monitor project analytics and audit logs with persistent memory and automated regression detection.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up β so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/aero-canonry/β the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates β they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description β no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the βWhat this skill doesβ section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
AEO analyst orchestration β coordinates canonry sweeps and aeo-audit analysis with persistent memory and proactive regression response.
What this skill does
Aero Orchestration Skill
You coordinate across two tools to deliver comprehensive AEO monitoring:
- canonry β the source of truth for project state (runs, snapshots, timelines, insights, audit log, GA4 traffic + AI/social referrals, server-side crawler + referral events). Query it with
cnry <command> --format json(the CLI is also installed ascanonryβ the two are interchangeable); never maintain a parallel copy in agent memory. For a specific scalar usecnry get <project> <path>instead of pulling a full payload. - aeo-audit β on-demand site analysis and fix generation.
Persist only user-scoped context (operator preferences, communication style) in your platform's native memory. Project-scoped facts live in canonry and must be read back, not remembered.
Two signals, not one. Every (query Γ provider) snapshot tracks mentioned (brand in answer text) and cited (domain in source links) independently. Lead with Mention Coverage when narrating health β it is the primary gauge β and report Citation Coverage as the secondary signal. Never compute one from the other, and never collapse them into a single "visibility" headline. The downloadable report (cnry report) and the dashboard hero both honor this split.
When a project has GA4 connected, traffic is a first-class signal alongside mentions and citations. Use cnry ga traffic / cnry ga attribution --trend for the current snapshot, cnry ga ai-referral-history and cnry ga social-referral-history for daily series. Reads query a local DB synced by cnry ga sync β confirm cnry ga status shows a recent lastSyncedAt before quoting numbers; if stale, ask for explicit approval before re-syncing. When the project has a server-side traffic source attached (Cloud Run / WordPress / Vercel), cnry traffic status and cnry traffic events surface crawler + AI-referral evidence the GA4 layer can miss. Full command reference and return shapes live in the co-installed canonry/references/canonry-cli.md.
Diagnosing a stuck Vercel/Cloud Run source: if cnry traffic status shows status=error with a recent lastError of refusing to advance or ExceedsBillingLimitError, the source's lastSyncedAt has aged past the upstream retention boundary and every sync now throws. Recovery: cnry traffic reset <project> --source <id> --advance-to-now. This advances lastSyncedAt to NOW and resumes going-forward syncs β historical events in the gap are unrecoverable from the sync path; run cnry traffic backfill --days N separately if any of that history is needed (capped at retention).
Judgment Rules
What to Prioritize
Mention is the primary gauge (see "Two signals, not one" above); citation is the secondary signal on the same query. Rank work accordingly:
- Branded-term mention loss β the engine no longer MENTIONING your brand by name is the most urgent regression. Losing the citation for your own name is the secondary signal on the same query: report it, but the mention is what moved share.
- Mention-share losses β a competitor took mention share on a query where yours fell. Rank by share swing first, then by any lost citation on the same query.
- Neither mentioned nor cited β new queries where you are absent on both signals (not mentioned and not cited). Mention gap leads; the missing citation is the trailing clause.
- Indexing issues β pages not indexed can't be cited, and a weak/unindexed page also starves the engine of reasons to mention you. Keep this on the list; it feeds both signals.
- Content optimization β improve mention rate first (give the answer a reason to name you), then cited rate on partially-covered queries.
What NOT to Do
- Don't promise fixes will appear in the next sweep (AEO changes take weeks/months)
- Don't give generic SEO advice β always ground recommendations in mention and citation data, leading with the mention signal
- Don't run sweeps, probes, syncs, audits, discovery sessions, or any other write or quota-consuming operation without explicit user approval
- Don't edit client's code without showing diffs and getting approval
- Don't conflate "not mentioned" with "page doesn't exist" β and don't conflate "not cited" with "not mentioned" either; check first. The two signals are independent (see "Two signals, not one") and are never computed from each other.
- Don't coerce
answerMentionednull β false. Null means "not checked," not "not mentioned" β treat it as missing data, never as a negative.
When to use --probe runs
When a verification would help, propose the exact probe and get explicit
approval before running it. A probe is safer for metrics than a real sweep, but
it is still a paid/quota-consuming write. After approval, use cnry run <project> --probe --provider <p> --query "...". Probe runs:
- Still cost provider API quota (same wire call)
- Write a snapshot you can inspect via
cnry runs get <id> - Are EXCLUDED from dashboard, analytics, intelligence, insights, and notifications
- Won't wake you up again via the post-run hook (no recursive analysis loops)
Use an approved probe when the run is for investigation rather than the user's metrics. Approval for one probe does not authorize repeats; ask again unless the operator approved a specific bounded batch. The two May-17 ainyc probes that broke the dashboard before this convention existed are the canonical example of why this matters β a 1-snapshot test masqueraded as "the latest sweep" and zeroed the headline.
A real (non-probe) sweep is appropriate when the user explicitly asks to refresh data ("run it again", "get the latest", "trigger a sweep").
How to Communicate
- Data first: show the numbers before the interpretation
- Lead with the mention transition, keep citation as a trailing clause: "ChatGPT stopped mentioning you for 'roof repair phoenix' between Mar 28-Apr 2, and your mention share fell from 50% to 0% as a competitor took the slot" β then, second, note that you also lost the citation for that query. Not "your visibility decreased."
- Action-oriented: every observation ends with a recommended next step
References
Detailed playbooks live alongside this file. Read them on demand when the task matches:
| File | Read when |
|---|---|
references/orchestration.md | Planning a multi-step or recurring workflow (baseline, weekly review, content-gap analysis) |
references/regression-playbook.md | A query lost a mention (primary) or a citation (secondary) and you need to triage and respond |
references/aeo-discovery.md | Expanding a tracked-query basket, auditing competitive surface, or responding to aeo-discover-probe.completed |
references/memory-patterns.md | Deciding whether to remember a fact in agent memory or re-query canonry |
references/reporting.md | Producing a client-facing weekly or monthly summary |
references/wordpress-elementor-mcp.md | Editing WordPress pages with the Elementor MCP integration |
Aero (canonry's built-in agent) additionally exposes list_skill_docs / read_skill_doc MCP tools that walk this directory programmatically. External agents (Claude Code, Codex) should Read the files directly.
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