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 adologyai/content-intelligence-plugin --skill brand-partnership-vettinggit clone --depth 1 https://github.com/adologyai/content-intelligence-pluginWrote 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/adologyai/content-intelligence-plugin/brand-partnership-vetting)<a href="https://agentmods.dev/skills/adologyai/content-intelligence-plugin/brand-partnership-vetting"><img src="https://agentmods.dev/badge/skills/adologyai/content-intelligence-plugin/brand-partnership-vetting/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/adologyai/content-intelligence-plugin/brand-partnership-vetting"><img src="https://agentmods.dev/badge/skills/adologyai/content-intelligence-plugin/brand-partnership-vetting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00186 | $0.13788 |
| Opus 5 | $0.00093 | $0.06894 |
| Sonnet 5 | $0.00037 | $0.02758 |
| Haiku 4.5 | $0.00019 | $0.01379 |
Grade A, and why
brand-partnership-vetting scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
direct `curl` / `wget` calls against scraper CDNs; the How it starts
The opening of the file, as written. The whole thing — 832 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Partnership Vetting & Selection
Self-contained skill. Everything you need — methodology, full HTML production template with CSS, section-by-section guidance — is in this file.
What This Skill Does
Takes a partnership brief, sources or evaluates candidate partner brands, scores them on observable content signals across seven weighted dimensions, and produces ranked scorecards with adapted partnership briefs and positioning implications for top picks. Final deliverable is an editorial HTML report a CMO or BD lead can print and circulate.
What You Can and Cannot Assess
Content intelligence shows you: brand voice and emotional register, existing partnership behavior, audience lifestyle signals, cultural currency, competitor precedent when triangulating against the focal brand's category peers.
Content intelligence cannot tell you: verified audience demographics, partnership pricing or commercial terms, partnership-team responsiveness, past partnership performance or conversion lift, active pipeline partnerships not yet in market, legal or compliance conflicts, whether content overlap translates to purchase behavior.
This is why every report ends with a "Verify Externally" checklist — flagging exactly what the user must check through other means.
Phase 1: Partnership Brief Intake
Partner-fit is entirely relative to the brief. Don't proceed without these inputs.
Required: focal brand name, partnership goal, target audience (specific, not "Gen Z"), focal brand voice posture.
Strongly recommended: use cases to amplify, partner archetypes of interest (earn money / spend money / manage habits / relieve bill stress / aspiration unlock / cultural moment), competitive context, partnership budget tier, number of picks.
Optional but valuable: existing partnerships to avoid, must-haves, dealbreakers, internal stakeholder for the deliverable.
If the user just drops brand names without a brief, ask for the brief. Be friendly: "Before I vet these, I need to understand the partnership strategy so I can score them against something real."
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 832 lines · 186 tokens per session scan A b2fb799478f5
brand-partnership-vetting is a skill published in the GitHub repository adologyai/content-intelligence-plugin (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 186 tokens to every session and 13,788 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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