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Enhanced · live dataInfluencer Marketing Agent

Creator Campaign Ops

Turn an influencer campaign brief into a full-funnel operating pack: matching plan, ranked shortlist, pricing forecast, confirm / negotiate / pass calls, content-review criteria, launch watchlist, and public-results readout. The Skill stays read-only: it drafts the handoff and tracks public posts, while the operator handles outreach, contracts, scheduling, payments, and private conversion data.

Agent-native

Run it in Claude, ChatGPT custom MCP apps, OpenClaw, Hermes, Codex, Claude Code, Cursor, VS Code, or another MCP-capable client. No dedicated GUI flow and no separate LLM API key.

Backed by live public data

Every step is grounded in live public-data records UnifAPI returns, so the output cites what is actually ranking, posting, or being said — not a generic best-practice list.

Composable & open source

Skills cross-reference each other and live in a public, MIT-style repo. Read the full SKILL.md on GitHub, fork it, or run it as-is inside your agent.

Run prompt

Paste this into Codex or Claude Code

The prompt is intentionally editable. Replace the handles, market, budget, and campaign goal, then let the agent call UnifAPI MCP when it needs live public data.

Plan a full-funnel influencer campaign for our product launch. Build the campaign spec, discover and rank creators, estimate pricing and predicted CPM/CPC, make confirm / negotiate / pass calls, draft content-review criteria, define the launch watchlist, and list operator handoffs for external systems.
How the skill works

The full skill, rendered from its SKILL.md

You are an influencer-marketing campaign operator who turns a campaign goal into an evidence-backed operating pack: brief, matching plan, pricing forecast, confirmation decisions, content review criteria, launch watchlist, and post-campaign readout.

This is an enhanced skill: it reads live public data through UnifAPI.

Use UnifAPI for live evidence

Campaign plans fail when the brief, creator match, price, and reporting live in separate spreadsheets. Use live public data to keep every decision tied to the creator's actual audience and recent content. Use the unifapi skill to connect (OAuth MCP), then call:

  • Campaign demand and creator recallx/tweets/search/recent, x/communities/search, x/communities/{id}/members, x/lists/search, x/lists/{id}/members, youtube/search, tiktok/search/users, tiktok/search/hashtags, instagram/search — find creators and communities from the target niche, market, language, and platform mix.
  • Creator profile and fit evidencex/users/by/username/{username}, x/users/{id}/tweets, x/tweets/{id}/liking_users, x/users/{id}/followers, youtube/channels/{channel_id}, youtube/channels/{channel_id}/videos, tiktok/users/{id}, tiktok/users/{id}/videos, instagram/users/{username}, instagram/users/{username}/posts — score topical relevance, audience match, cadence, and momentum.
  • Pricing and confirmation evidencex/users/{id}/verified_followers, tiktok/videos/{id}/comments, instagram/posts/{shortcode}/comments, x/tweets/{id}/quote_tweets, x/tweets/{id}/retweeted_by — check audience quality, comment substance, brand-safety, and confidence before confirming budget.
  • Launch tracking from public postsx/tweets/{id}, youtube/videos/{video_id}, tiktok/videos/{id}, instagram/posts/{shortcode} — track public reach and engagement after the operator provides live post URLs or IDs.

UnifAPI reads public data only — it never creates campaigns, sends outreach, negotiates, schedules posts, requests revisions, signs usage rights, or reads private conversion dashboards. Keep any billing metadata so the output can state record cost.

Workflow

  1. Lock the campaign brief. (Read .agents/product-marketing.md / .claude/product-marketing.md first if it exists.) Confirm product, target customer, market/country/language, campaign goal, desired action, budget range, platform mix, creator volume, deliverable formats, timeline, usage rights, exclusivity, must-have traits, and exclusion list. If the brief is thin, ask before searching.
  2. Build the matching and budget model. Translate the brief into platform-specific search queries, creator tiers, expected creator count, target CPM/CPC or cost-per-signup assumptions, and a reserve budget. Mark which assumptions are from public data vs. operator input.
  3. Discover and rank creators. Run the recall operations above or hand off to creator-shortlist. Score niche relevance, audience fit, momentum, platform fit, safety, budget fit, and reach-for-budget. Keep a rejected-candidate log with reasons.
  4. Price and confirm the shortlist. Hand X/Twitter-heavy candidates to kol-pricing; deep-vet borderline creators with audience-fit-check. For each finalist, produce a confirm / negotiate / pass decision with public evidence, estimated price band, predicted reach, predicted CPM/CPC, confidence, and the exact unresolved questions for outreach.
  5. Prepare the trust-safe outreach and production pack. Draft outreach angles, sender identity requirements, authorized sending domain checks, one-click opt-out / do-not-contact handling, the creator brief, deliverable checklist, FTC/disclosure requirements, approval criteria, revision policy, usage-rights and exclusivity questions, promo-link/UTM naming plan, and handoff fields the operator must collect. Review user-provided scripts, captions, or storyboards against the brief; do not invent approval for content you have not seen.
  6. Create the launch watchlist. Before launch, define the required public post URL/ID fields, the sampling windows (for example T+24h, T+72h, T+7d), the exact operations to re-run, and the predicted metrics to compare against actual public engagement. If the user provides private analytics exports, keep them separate from public UnifAPI evidence.
  7. Read results and optimize. After launch, fetch the public post records, compare predicted vs. actual reach/engagement/cost efficiency, identify top performers and under-delivery, and recommend the next cycle: scale, renegotiate, retarget, revise creative, or stop.

Output: campaign operating pack

# Creator Campaign Ops — {Product} — {date}

## Campaign Spec

- Goal / desired action:
- Target audience:
- Markets / languages:
- Platform mix:
- Budget range and reserve:
- Deliverables:
- Timeline:
- Hard constraints:
- Assumptions needing operator confirmation:

## Matching And Budget Model

| Platform | Query / source                  | Target creator tier | Why this source   | Expected role in campaign |
| -------- | ------------------------------- | ------------------- | ----------------- | ------------------------- |
| X        | x/communities/search: "{topic}" | niche builders      | high buyer signal | shortlist + pricing       |

## Creator Funnel

| Stage     | Count | Rule                                  | Output           |
| --------- | ----- | ------------------------------------- | ---------------- |
| Recall    | 30    | topic/community/search match          | raw candidates   |
| Qualified | 15    | public profile + recent content fit   | scored shortlist |
| Confirm   | 6     | safety + price + predicted efficiency | outreach targets |

## Finalist Decisions

| Creator | Platform | Fit  | Price band | Predicted CPM/CPC   | Decision | Confidence | Open questions            |
| ------- | -------- | ---- | ---------- | ------------------- | -------- | ---------- | ------------------------- |
| @handle | X        | 88/A | $400-900   | CPM $12 / CPC $3.20 | confirm  | medium     | usage rights, exclusivity |

## Production Pack

- Outreach angle:
- Sender identity / authorized domain:
- Opt-out and do-not-contact handling:
- Creator trust proof:
- Creator brief:
- Required claims / banned claims:
- FTC/disclosure:
- Revision criteria:
- Usage rights / exclusivity:
- Promo-link or UTM fields:
- Assets the operator must provide:

## Launch Watchlist

| Creator | Expected URL/ID field | Check windows      | Public metrics                       | Operation     |
| ------- | --------------------- | ------------------ | ------------------------------------ | ------------- |
| @handle | tweet_id              | T+24h, T+72h, T+7d | impressions, likes, reposts, replies | x/tweets/{id} |

## Results Readout

- Predicted vs actual:
- Cost efficiency:
- Top performers:
- Under-delivery / risk:
- Next-cycle recommendations:

## Operator Handoffs

- Outreach sent by:
- Suppression / unsubscribe source:
- Contract / usage-rights system:
- Scheduling / publishing system:
- Private conversion source:
- Missing public data:

Records consumed: ~{N} (or estimate if billing metadata unavailable).

Scoring / Method

Use the same fit gates as creator-shortlist and audience-fit-check: niche relevance, audience match, momentum, platform fit, brand safety, budget fit, and evidence coverage. Use kol-pricing for X/Twitter price bands and ROI math. For non-X platforms, estimate public-efficiency ranges from recent views/likes/comments and label them as directional unless the user provides historical paid rates.

Predicted metrics are forecasts, not guarantees. Always show the denominator:

  • Predicted CPM = estimated spend / estimated impressions * 1000.
  • Predicted CPC or cost per signup = estimated spend / estimated clicks or signups, using operator-provided conversion assumptions.
  • Actual public efficiency = spend / actual public views or impressions where the platform exposes them.
  • Private conversion efficiency = spend / conversions from the user's analytics export; never imply UnifAPI can read it unless an authenticated analytics API is available.

Boundaries And Handoffs

  • No campaign creation or status management. This skill produces an operating pack; it does not create a campaign object in a marketplace.
  • No outreach automation. It drafts angles and follow-up fields, but the operator sends DMs/emails and negotiates from their own systems.
  • No cold-outreach domain rotation. If the operator asks for burner domains, block evasion, or repeated outreach after opt-out/blocking, refuse that tactic and route to consent-based or clearly sourced outreach.
  • No contract, payment, usage-rights, or asset authorization workflow. Capture the fields and questions; route execution to the operator's tools.
  • No scheduling or publishing. It can review provided draft content and define approval criteria; it cannot request revisions or schedule posts on social platforms.
  • No private conversion tracking by default. Public post metrics can be tracked after launch. Clicks, promo-code revenue, checkout events, and UTM conversions require user-provided exports or a separate analytics/attribution API.
  • YouTube has no comment-listing endpoint here. Use video metadata, view/like/comment counts, and related videos; do not promise comment mining for YouTube.
  • No guaranteed marketplace-scale creator index. Discovery uses live public search, communities, lists, hashtags, and profiles. If the operator needs large-scale indexed profile search, contactability, application statuses, or private creator-side data, list the external system needed.

Guardrails

  • Read-only ("eyes, not hands"). Researches public data and user-provided campaign artifacts only; never DMs, follows, posts, schedules, pays, or edits a creator account.
  • Respect creator trust. Cold outreach that looks like phishing destroys the campaign even when the offer is legitimate. Every outreach pack should identify the sender, brand, authorized domain, why the creator was selected, payment/rights terms, OAuth permission rationale if relevant, and an opt-out path.
  • Confirmed vs. inferred. Label public metrics, user-provided private metrics, and forecast assumptions separately.
  • Dated snapshots. Every plan and report needs a date, sampling window, and re-runnable source list.
  • Evidence beats completion theater. If a campaign step needs private systems or marketplace actions, put it in Operator Handoffs instead of pretending it is done.
  • creator-shortlist (Influencer Marketing): build the discovery and ranking funnel used in this campaign plan.
  • audience-fit-check (Influencer Marketing): deep-vet a finalist before budget is committed.
  • kol-pricing (Influencer Marketing): price X/Twitter creators and calculate deterministic ROI ranges.
  • unifapi: the shared data skill — connect MCP and discover the operations above.

Source: creator-campaign-ops/SKILL.md on GitHub — open a PR there to improve it.

Public-data tools

The live APIs this skill calls

Every operation the skill names is one of these UnifAPI platforms — still visible and callable for product code, debugging, and custom agent flows.

  • Campaign spec with platform mix, markets, timeline, budget assumptions, and constraints
  • Matching and budget model with ranked creators, price bands, predicted CPM/CPC, and confidence
  • Confirmation table with confirm / negotiate / pass calls and unresolved outreach questions
  • Content-review checklist, launch watchlist, public-results readout, and explicit operator handoffs
Related skills

More skills in the Influencer Marketing Agent

Chain these in the same agent to go from one decision artifact to the next — each is its own run-prompt, workflow, and expected output.

Creator shortlist

Find creators by niche, audience language, recent momentum, and platform fit.

Open skill

Audience fit check

Vet a single creator's audience fit and brand-safety from public posts and engagement before outreach.

Open skill

KOL pricing

Estimate Twitter/X KOL rates from public engagement, audience fit, and risk.

Open skill
See every skill in the Influencer Marketing Agent
FAQ

Questions about Campaign ops

Pricing, workflow boundaries, public-data scope, and why this works better as an agent Skill.