SuperAPI AI Directory

startup-channel-finder

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Updated 10-15 23:44

About this skill

Startup Channel Finder

Turn a startup URL or product description into an evidence-backed distribution plan. Recommend places where the intended audience is demonstrably active, not generic lists of popular launch sites.

Read references/research-playbook.md before researching. Read references/analysis-schema.md before writing the analysis JSON.

Resolve SKILL_DIR as the directory containing this SKILL.md. Run bundled scripts from SKILL_DIR, while writing all outputs into the user's current workspace.

Workflow

1. Understand the launch

  • Inspect the supplied URL, repository, landing page, README, or product description.
  • Identify product, primary ICP, painful job, differentiation, stage, geography, language, CTA, and launch goal.
  • Separate facts from inferences. Ask one concise question only when ambiguity would materially change the audience or market; otherwise continue with labeled assumptions.
  • Treat a feature launch differently from a company launch, waitlist, beta, open-source release, or paid-product launch.

2. Build a channel hypothesis map

  • Translate the ICP and painful job into search phrases, problem language, role names, alternatives, workflows, and buying or adoption triggers.
  • Search across several relevant channel types: communities, forums, directories, launch platforms, newsletters, marketplaces, social discussions, events, and niche publications.
  • Use current web research. Never rely on a bundled static list as proof that a channel is active or appropriate today.
  • Prefer original channel pages, official submission pages, official rules, and recent discussions over search-result snippets or third-party listicles.

3. Verify every candidate

For each candidate, record:

  • direct channel URL and channel type
  • evidence that the ICP is present
  • evidence that the target problem or workflow appears there
  • recent activity date when visible
  • official rules or submission instructions
  • promotion policy: allowed, conditional, prohibited, or unknown
  • best format, angle, CTA, timing, and principal risk
  • date on which the evidence was checked

Do not recommend a channel as actionable without direct audience evidence and a verified promotion or submission path. Mark unavailable facts as unknown; never invent audience size, reach, engagement, pricing, acceptance rate, or conversion potential.

4. Score deterministically

Score each factor from 0 to 5:

  • audience_fit — How closely the active audience matches the primary ICP.
  • pain_presence — How clearly the target problem or job appears in current discussions or channel positioning.
  • permission_fit — How compatible the launch is with official rules and accepted formats.
  • timing — How active and timely the channel is for this launch now.
  • effort_efficiency — Expected value relative to submission, participation, or production effort.

Write unscored research to outputs/startup-channel-analysis.json, then run:

python3 "$SKILL_DIR/scripts/score_channels.py" \
  outputs/startup-channel-analysis.json \
  outputs/startup-channel-scored.json

The script computes the weighted score, verification status, and recommended action. Do not manually override its result. Explain any research limitation rather than inflating a factor.

5. Use action labels precisely

  • POST_NOW — Strong fit, current evidence, and explicit permission for the intended format.
  • CONTRIBUTE_FIRST — Strong audience fit, but community participation or trust should precede promotion.
  • SUBMIT — A verified directory, marketplace, newsletter, publication, or launch platform with a suitable submission path.
  • SKIP — Weak fit, inactivity, prohibited promotion, unknown rules, insufficient evidence, or poor effort-to-value ratio.

Never convert SKIP into a recommendation merely to fill the report. Prefer three defensible channels over twenty generic names.

6. Draft for the channel

  • Create a distinct draft for each actionable top channel.
  • Match the accepted format, tone, title pattern, disclosure expectations, link policy, and CTA.
  • Ground the angle in the audience's job or problem; do not paste the landing-page headline everywhere.
  • Avoid fake personal familiarity, fabricated traction, engagement bait, mass posting, ban evasion, or pretending to be a satisfied user.
  • Keep drafts as suggestions. Do not post, submit, join, message, comment, or create accounts without a separate explicit request and authorization.

7. Build the launch sequence

  • Order actions by dependency and learning value, not only score.
  • Use early conversations and community feedback to improve later directory or platform launches.
  • Create a seven-day plan with one goal, concrete actions, required asset, and success signal per day.
  • Recommend manual tracking with channel, date, message variant, visits, signups, replies, qualified conversations, and relevant conversion event.
  • Keep expected outcomes as hypotheses unless the user supplies historical data.

8. Generate the native report

Create:

  • outputs/startup-channel-scored.json — machine-readable evidence, scores, and actions.
  • outputs/startup-channel-report.md — user-facing report that opens directly in Codex and renders on GitHub.
  • outputs/startup-channel-calendar.csv — execution sheet for the seven-day plan.

Run:

python3 "$SKILL_DIR/scripts/generate_report.py" \
  outputs/startup-channel-scored.json \
  outputs/startup-channel-report.md \
  --csv outputs/startup-channel-calendar.csv

Verify that every material claim and recommendation links to direct evidence. Return a clickable absolute link to the Markdown report.

Report order

  1. Launch verdict and strongest channel
  2. Product, ICP, goal, and assumptions
  3. Ranked channel table
  4. Detailed playbook for each actionable channel
  5. Seven-day launch calendar
  6. Tracking plan
  7. Skipped channels and reasons
  8. Evidence limitations and unknowns

Modes

  • quick — Research up to five candidates and draft for the strongest two.
  • standard — Research eight to twelve candidates across several types and build the full plan.
  • deep — Research up to twenty candidates with broader source diversity and contradiction checks.
  • community-first — Prioritize communities and trust-building before promotion.
  • directories-only — Prioritize verified submission platforms and directories.
  • launch-week — Prioritize an immediate seven-day sequence around a known launch date.

Use standard by default.

Quality bar

  • Link the product interpretation and every material channel claim to current public evidence.
  • Require direct audience evidence and a rules or submission source for actionable channels.
  • Make check dates, uncertainty, stale evidence, and contradictory signals visible.
  • Distinguish audience presence from proven conversion or willingness to pay.
  • Do not treat follower counts, member counts, or generic popularity as audience fit.
  • Do not recommend prohibited promotion, private groups without access, scraped contact lists, or automated cross-posting.
  • End with a sequence the founder can execute manually, not merely a list of websites.