suede-influencer-outreach

suede-influencer-outreach is a skill for Claude Code, Codex from JasonColapietro/suede-creator-skills. It costs 108 tokens per session (2,594 once invoked), scanned A, original, MIT.

A personalised outreach workflow helps write a first message to one vetted creator, newsletter writer, or podcaster. It uses a named piece of their work or an audience fact and states the actual payment or offer.

In plain words
What is it for?
Use it to contact an influencer or other creator about a promotion or partnership. It helps prepare the pitch, offer details, and handoff if the person agrees.
Why use it?
It avoids generic pitches and unclear compensation. It also keeps the request small and gives the conversation a defined follow-up path.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the suede-marketing plugin — 40 skills shipped together , and of suede-skills

Good fit Use it to contact an influencer or other creator about a promotion or partnership. It helps prepare the pitch, offer details, and handoff if the person agrees.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jasoncolapietro/suede-creator-skills/suede-influencer-outreach
Install

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.

Any agent
npx skills add JasonColapietro/suede-creator-skills --skill suede-influencer-outreach
Clone the repo
git clone --depth 1 https://github.com/JasonColapietro/suede-creator-skills

Made for: Claude Code, Codex.

Or install suede-marketing, the plugin that ships this one along with the rest of its 40 skills.

Wrote 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.

agentmods badge for suede-influencer-outreach

README.md
[![agentmods](https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-influencer-outreach/github.svg)](https://agentmods.dev/skills/jasoncolapietro/suede-creator-skills/suede-influencer-outreach)
Your own site
<a href="https://agentmods.dev/skills/jasoncolapietro/suede-creator-skills/suede-influencer-outreach"><img src="https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-influencer-outreach/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.

agentmods 80×15 button for suede-influencer-outreach

Your own site · 80×15
<a href="https://agentmods.dev/skills/jasoncolapietro/suede-creator-skills/suede-influencer-outreach"><img src="https://agentmods.dev/badge/skills/jasoncolapietro/suede-creator-skills/suede-influencer-outreach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 108 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,594 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00108 $0.02594
Opus 5.5 $0.00043 $0.01038
Sonnet 5.5 $0.00022 $0.00519
Haiku 4.5 $0.00011 $0.00259

Measured today against content hash 2cfc379356cc, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

suede-influencer-outreach 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 today.

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.

skills/suede-influencer-outreach/SKILL.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Suede AI Influencer Outreach Skills

Write the first message a creator actually answers. One vetted creator, one pitch, a short follow-up plan, and a clean handoff the moment they say yes.

Compatibility

Any agent with a vetted creator, cited audience evidence and approved compensation details. Current contact-route checks need web access; drafts need no sending or social integration.

Before Writing

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use it for brand, product, voice, and signer, and only ask for what it does not cover.

Collect these, one question per message, multiple choice where it helps. Skip anything already answered.

  1. B2C or B2B? Product sold to consumers, or to businesses. This sets the framing and the deliverable types.
  2. What does the brand make, and why would this creator's audience care? One line.
  3. Who is the creator, on which platform, and what is the fit evidence? A named post, a series, an audience trait, or a media kit. Fit evidence is input from the user or from your own reading of their work. Never invent it.
  4. What is the offer, with the real number? Flat fee, commission (rate, attribution window, payout schedule), gifted product or access, or a hybrid. This skill states the offer. It does not set or change it.
  5. Rough deliverable and timing. One line, enough to sketch.
  6. Which contact does the creator publish? Business email, DM only, or a manager or agent.
  7. Brand voice and signer. Formal, peer-casual, or playful. A named person signs.
  8. Which ask can the brand honor this week? Reply for details, a sample or trial on reply, a short call, or an application link.
  9. Deadline and intent. Is there a launch date to beat? Is this a one-off, or a relationship worth building?

After the answers, say which answer moved which default below. An existing relationship with the creator or their manager, a brand they already recognize, audience data in hand, or nothing to gift all change the order.

Read the full file on GitHub · 201 lines

Files

What ships with it

8 files 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.

Changes

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.

  1. today Changed · +9 lines · -85 tokens per session 2cfc379356cc
  2. yesterday First seen · 192 lines · 193 tokens per session scan A f04baeb19c87

Subscribe to this mod's changes

suede-influencer-outreach is a skill published in the GitHub repository JasonColapietro/suede-creator-skills (126 stars, last pushed today), licensed MIT. It adds 108 tokens to every session and 2,594 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-26.

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