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/logly/mureo/onboardnpx skills add logly/mureo --skill onboardgit clone --depth 1 https://github.com/logly/mureoWhat 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 | $0.00099 | $0.03627 |
| Opus 5 | $0.00049 | $0.01813 |
| Sonnet 5 | $0.00020 | $0.00725 |
| Haiku 4.5 | $0.00010 | $0.00363 |
Grade A, and why
onboard 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Onboard
PREREQUISITE: Read
../_mureo-shared/SKILL.mdfor auth, security rules, output format, and Tool Selection (Read/Write on Code,mureo_strategy_*/mureo_state_*MCP on Desktop / Cowork).
Guide me through setting up mureo for a new marketing account.
Steps
-
Check installation: Verify mureo is installed by running
mureo --help. If not found, guide the user to runpip install mureo. -
Check data mode (BYOD first, then auth):
Always run
mureo byod statusfirst. If any platform showsBYOD (N rows, ...), that platform is in BYOD mode — do NOT prompt the user to runmureo auth setupfor it, do NOT callmureo auth statusto "verify" it (that command readscredentials.jsondirectly and ignores BYOD), and do NOT report it as "未認証". For BYOD platforms, announce: "Using BYOD CSV data (N rows, )."For the remaining platforms (those showing
not configuredorreal API), then runmureo auth statusto see which have OAuth credentials. If a platform isnot configuredfor BYOD AND has no credentials, offermureo auth setup(interactive — user runs it themselves) or offer the BYOD path: "Export a CSV from and runmureo byod import <file>instead."Never claim a platform is unauthenticated when
mureo byod statusshows it in BYOD mode. BYOD takes priority over OAuth and is sufficient on its own for analysis.Note: When calling MCP tools, you do NOT need to specify customer_id or account_id — they are automatically loaded from credentials.json (real API mode) or routed to the BYOD client (BYOD mode). Just omit them.
-
Create STRATEGY.md: Ask me about my business to fill in each section:
- Persona: Who is the target customer? (role, age, goals, pain points)
- USP: What makes the product/service unique? (3-5 bullet points)
- Target Audience: Demographics, geography, budget range
- Brand Voice: Tone and style guidelines for ad copy
- Market Context: Competitors, market trends, competitive advantages
- Operation Mode: Choose from the imported campaigns' actual
maturity, NOT from the fact that mureo was just set up:
- Use
ONBOARDING_LEARNINGonly for genuinely new campaigns still in their learning period — little/no accumulated conversions and started recently (roughly the last 2-4 weeks). - For campaigns that have already been running for a while with
accumulated conversion history, pick a steady-state mode — default to
EFFICIENCY_STABILIZE(mature campaigns optimizing for efficiency), or another mode the imported data clearly warrants (e.g.SCALE_EXPANSION,TURNAROUND_RESCUE). - Base this on real delivery data, not setup recency: use the recent
conversion volume from
google_ads_performance_report(LAST_30_DAYS) and the learning status fromgoogle_ads_campaigns_diagnose— i.e. the data fetched in step 7 below. If you reach this step before that data is available, fetch it now (or finalize the mode right after the step-7 diagnosis). STATE.json's campaign snapshots do not carry age / conversion counts, so do not rely on them for this. If still unsure, ask me. PickingONBOARDING_LEARNINGfor a long-running campaign makes the first daily-check wrongly tell me to "prioritize data accumulation" when the data is already there.
- Use
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 · 127 lines · 99 tokens per session scan A a4e3a6048cd7
onboard is a skill published in the GitHub repository logly/mureo (42 stars, last pushed 3d ago), licensed Apache-2.0. It adds 99 tokens to every session and 3,627 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 2026-08-30.
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