marketing-os-research
De la autor
Answer an open question the Marketing OS already wrote down, then promote it to a finding. Takes its queue from the OS itself: files with status open-question in Intelligence/research/, open questions and untested beliefs in Analytics/what-works.md, and ideas with no established pain. Fans out one agent per stream in a single batch across papers, forums, the web and creators, with an effort floor, distinct sources and full-text reads, fact-checks every hard claim with a verifier prompted to refute rather than confirm, then writes Intelligence/research/topic-slug.md and updates the question file in place with a dated status change. Routes findings about our own performance to Analytics, and graduates recurring customer language to the segment files. Always closes by rendering the report. Use when the user says 'research this', 'deep dive on', or runs /marketing-os-research.\" disable-model-invocation: true argument-hint: \"[a topic, or an open-question file to close, or nothing to be shown the queue]
Instalare
npx skills add naveedharri/benai-skills --skill marketing-os-research -a claude-code
Se instalează în .claude/skills/marketing-os-research/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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De ce 82
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- marketing-os-newsletternaveedharri/benai-skillsWrite a newsletter edition from the Marketing OS, gated step by step, then file it as a real asset. Reads the ICP, voice register, offer and live price, measured patterns and swipe file from the OS, never from bundled copies. Sources from a pillar asset, the values doc, a community post or a raw idea. Fans out five parallel readers over the OS before the first gate, and verifies the draft with independent agents against the voice register and offer facts. Seven gates with options at each; the edition is written only after the angle, insight, outcome, outline, subject line and hook are confirmed. On approval it writes Channels/newsletter/broadcasts/YYYY-MM-DD-slug.md, appends the shipped subject line to the swipe file, updates the parent's repurpose tree, logs, and always closes by rendering the edition. Use when the user says 'write a newsletter', or runs /marketing-os-newsletter.\" disable-model-invocation: true argument-hint: \"[source, e.g. a published video slug, 'values doc', or a raw idea]Marketing★ 74
- research-opsericrisco/rsc-harnessUse when someone hands you an open question whose answer must survive scrutiny — a tech choice, a regulation, a what-is-actually-true-about-X — with every non-obvious claim dated and sourced, source disagreements surfaced rather than averaged away, and a cited memo as the deliverable. Also for refreshing a stale research memo. NOT sizing a market with TAM/SAM/SOM (that is `market-research`), NOT a standing cadence watch on named rivals (that is `competitor-watch`).Știință★ 272
- marketing-os-routinesnaveedharri/benai-skillsCreate and manage the Marketing OS routines as scheduled tasks: ten of them in two groups: five operating routines (morning performance sweep, content pipeline sync, campaign sync, dashboard, monthly report) and five intelligence and review routines (market scan, customer intel, competitor radar, pipeline hygiene, quarterly report). Probes every connector first and reports exactly what each routine loses without it, so nothing gets scheduled against a dead integration. Gives the operator the schedule, the connector list, and the prompt to paste for each. Every routine is independent and none depends on another having run. Use when the user says 'register my marketing routines', 'schedule the marketing OS routines', 'set up marketing automation', 'which routines should I turn on', 'my routines are not running', 'marketing os routines', or runs /marketing-os-routines.Marketing★ 74
- marketing-os-setupnaveedharri/benai-skillsSet up a Marketing OS: a markdown second brain that becomes the single source of truth every marketing skill reads, plus the routines that keep it current and a control-center dashboard on top. Interview-driven and idempotent, safe to re-run. Builds seven knowledge folders (Context, Channels, Campaigns, Offers, Analytics, Team, Intelligence) plus Routines, writes the Context layer that ends skills carrying their own stale copies of the ICP and offer and voice, scaffolds one folder per publishing surface, then offers to set up the routines via marketing-os-routines and to build the control center via marketing-os-dashboard. Walks five pillars in order: connectors, Context, structure, routines, dashboard. Use when the user says 'set up a marketing OS', 'build my marketing second brain', 'marketing os setup', 'install the marketing OS', 'I want a marketing operating system', 'give my marketing skills real context', or runs /marketing-os-setup.Marketing★ 74
- deep-researchcoreyhaines31/makerskillsWhen you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any "I need to actually understand X." Combines web search, URL fetch, agent-browser, last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on "/deep-research," "research X," "investigate X," "do a deep dive on X," "look into X," "what's actually happening with X," "due diligence on X," "validate this market." Differs from a one-shot web search: this is multi-pass with verification. Not for standing monitoring (radar) or pulling one post or video (social-fetch, watch-video).Știință★ 873
- ml-autoresearchgaasher/Agent-Loop-SkillsUse when the user wants an autonomous ML research loop that does more than blindly try changes. After every training run the agent analyses what actually happened inside the model — gradients, activations, embeddings, errors, data — and grounds the next change in that evidence. A `<literature>` on/off dial adds scientific-literature grounding: off behaves as a pure analysis-first loop; on searches papers, grades the evidence, and implements only what prior work supports. One change per run; loops forever until interrupted. Not for one-off training runs or hyperparameter sweeps.Știință★ 177
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