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 skills add cogni-work/insight-wave --skill marketing-resumegit clone --depth 1 https://github.com/cogni-work/insight-waveWrote 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/cogni-work/insight-wave/marketing-resume)<a href="https://agentmods.dev/skills/cogni-work/insight-wave/marketing-resume"><img src="https://agentmods.dev/badge/skills/cogni-work/insight-wave/marketing-resume/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/cogni-work/insight-wave/marketing-resume"><img src="https://agentmods.dev/badge/skills/cogni-work/insight-wave/marketing-resume.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00090 | $0.01036 |
| Opus 5 | $0.00045 | $0.00518 |
| Sonnet 5 | $0.00018 | $0.00207 |
| Haiku 4.5 | $0.00009 | $0.00104 |
Grade A, and why
marketing-resume 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 7d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Resume
Purpose
Re-enter an existing marketing project, display comprehensive status, and recommend the highest-priority next action. Designed for multi-session workflows where the user returns after days or weeks.
Workflow
Step 1: Discover Projects
Glob for **/marketing-project.json in the working directory. If multiple found, present list and ask user to select. If one found, load automatically.
Step 2: Status Assessment
Read all project files and compute:
-
Project health:
- Sources connected: ✅/❌ for portfolio and TIPS
- Markets configured: count
- GTM paths mapped: count
- Brand configured: ✅/❌
-
Content strategy status:
- Strategy defined: ✅/❌
- Total planned pieces: count
- Generated pieces: count (by scanning content/ directories)
- Coverage percentage: overall and per market
-
Campaign status:
- Active campaigns: count
- Campaign phase: attract/engage/convert
- Content gaps blocking campaigns: list
-
Calendar status:
- Calendar exists: ✅/❌
- Upcoming deadlines: next 7 days
- Overdue items: any with past dates still in "planned" status
Step 3: Present Dashboard Summary
cogni-marketing: {project_name}
Brand: {brand_name} | Language: {language}
Portfolio: {portfolio_path} | TIPS: {tips_path}
Markets & Coverage:
mid-market-saas-dach: ████████░░ 78% (14/18 pieces)
enterprise-mfg-dach: ████░░░░░░ 40% (6/15 pieces)
Campaigns:
ai-pred-q2: Phase 2/3 (Engage) — 8 touchpoints done, 4 remaining
cloud-native-awareness: Phase 1/3 (Attract) — just started
Content by Type:
Thought Leadership: 5/6 ████████░░
Demand Generation: 8/12 ██████░░░░
Lead Generation: 3/8 ████░░░░░░
Sales Enablement: 2/5 ███░░░░░░░
ABM: 2/2 ██████████
Calendar:
⚠️ 2 items overdue (linkedin-post Apr 10, email-nurture Apr 12)
📅 Next: blog publication Apr 15
Step 4: Recommend Next Action
Based on priority logic:
- Overdue content → Highest priority. "Generate the overdue LinkedIn post for campaign X."
- Campaign blockers → Content gaps blocking the next campaign phase. "Generate whitepaper to unblock Phase 2 of ai-pred-q2."
- Lowest coverage market → "Enterprise-mfg-dach is at 40% — start with thought leadership blog."
- Funnel gaps → "You have 8 awareness pieces but only 2 decision pieces — generate battle cards."
- New content from strategy → Next item in priority sequence from content-strategy.
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.
- 7d ago First seen · 107 lines · 90 tokens per session scan A 7de238598fcc
marketing-resume is a skill published in the GitHub repository cogni-work/insight-wave (13 stars, last pushed today), licensed Apache-2.0. It adds 90 tokens to every session and 1,036 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 2026-09-04.
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