Systems Lab

Agent skill

channel-strategy

Identify and prioritize go-to-market channels using Weinberg's Bullseye Framework, CAC/LTV-per-channel math, channel-fit-by-ICP scoring, and stage-appropriate selection.

slowingNeeds a keyActs undeclared1,007 words

Filed under Partnerships and channel.

From devangk003/gtm-agent-skills · 32 skills · 0 · pushed 2026-06-18

What it does when it runs

Identify and prioritize go-to-market channels using Weinberg's Bullseye Framework, CAC/LTV-per-channel math, channel-fit-by-ICP scoring, and stage-appropriate selection. Produces a focused 1–3 channel bet with experiment design and kill criteria. Use when the user says "which channels should we use", "we're doing too many channels", or "should we try TikTok for B2B.

Read from the skill and the 6 files bundled beside it. A skill’s own description is written to be selected by an agent, so it describes the job and not the dependencies.

Keys and connectors you must supply
  • AGENTIC_APP_TOKEN
Hosts it reaches
No third-party host appears in the skill or its bundled files.
Tool permissions it declares
No allowed-tools in the frontmatter. It does act, so it runs under whatever permissions your session already grants.
Actions present in the files
shell

Ask about channel-strategy

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Rather ask a human? Talk to Cheetah
git clone --depth 1 --filter=blob:none --sparse https://github.com/devangk003/gtm-agent-skills.git /tmp/gtm-agent-skills
git -C /tmp/gtm-agent-skills sparse-checkout set "channel-strategy"
mkdir -p ~/.claude/skills/channel-strategy
cp -R "/tmp/gtm-agent-skills/channel-strategy/." ~/.claude/skills/channel-strategy/

Picked up without a restart. A project skill of the same name is shadowed by your personal one. For one repository only, swap ~/.claude/skills for .claude/skills. Claude Code docs ↗

The folder is the same in every client that implements the format — 46 of them — so if yours is not above, only the destination changes.

Before you install: this skill will not complete its job on a bare agent. It needs AGENTIC_APP_TOKEN, which you have to obtain separately.

Reproduced in full from devangk003/gtm-agent-skills/blob/6b9a1b0094ffd83d6c02bc03b7ce1610661a1644/channel-strategy/SKILL.md, which is licensed MIT (skill frontmatter). 1,007 words, 10 headings.

Channel Strategy

Decide where to spend GTM time, energy, and budget. Replace channel-by-familiarity with structured analysis: 19 channels evaluated, ICP-fit scored, CAC/LTV checked, Bullseye plan delivered with experiment design and kill criteria.

Framework(s) used: Bullseye Framework + 19-channels list (Weinberg/Mares Traction) — Bullseye for prioritization, 19-channels as the canonical channel taxonomy. If multiple frameworks apply, trigger Clarification Protocol so the user picks.

Clarification Protocol

When you encounter any of the following, STOP and ask the user — do NOT make a silent assumption, and do NOT flatly refuse:

  • Ambiguous or missing input
  • A fork in approach (multiple valid frameworks, segments, scopes, or sources)
  • A rule that would block progress
  • An assumption that materially shapes the output
  • Unverified data that a downstream step depends on

Present 2–4 concrete options with trade-offs and your recommendation.

Format:

Decision needed: <what's being decided> Options:

  • A) <option> — trade-off
  • B) <option> — trade-off
  • C) <option> — trade-off My recommendation: <X> because <reason>. Confirm or pick a different option before I continue.

Refusing to proceed is NEVER the final answer. Every "block" must come with an override option. If the user picks an override, honor it on the first request — do not re-prompt the same block multiple times in one run.

Scope

This skill ONLY produces GTM channel prioritization (Bullseye-style channel matrix with effort, fit, and CAC estimates). Do not expand into adjacent topics. If the user's request implies adjacent scope, trigger Clarification Protocol with options to (A) stay in scope, (B) note the adjacent need as a follow-up, (C) hand off to a different skill.

Verification Requirements

Before producing the final output, every factual claim about external entities (markets, competitors, people, companies, technologies, pricing, benchmarks) MUST be verified via web search.

  • Use a quick lookup for single-fact checks (one company, one stat).
  • Use a deep search for landscape/trend questions (multi-source synthesis).
  • Tag every verified claim inline as [H/M/L][Sn].
  • End the report with a ## Sources section.
  • Unverified claims belong in ## Assumptions to Validate, NOT in the main analysis.

Sources are mandatory. If you cannot cite a source for a factual claim, do not state it as fact — move it to Assumptions to Validate or trigger Clarification Protocol.

Per-channel verification rule: every channel claim (CAC range, audience size, conversion benchmark) must be web-verified or marked [UNVERIFIED] and surfaced in Assumptions to Validate.

When to Use

  • User asks "Which channels should we use?" or "We're doing too many — what to cut?"
  • Budget allocation across channels or new-channel evaluation
  • Stage transition ("We're at $1M ARR — should we add channels?")
  • Underperformance diagnosis ("Channel X isn't working — should we kill it?")
  • Pre-fundraise channel narrative

Quick Reference

ConceptDetail
19 Bullseye channelsTargeting blogs · Publicity · Unconventional PR · SEM · Social ads · Offline ads · SEO · Content · Email · Eng-as-marketing · Viral · BD · Sales (outbound) · Affiliate · Existing platforms · Trade shows · Offline events · Speaking · Community
Bullseye ringsOuter (19 considered) → Middle (3 tested, ≤$1k each) → Inner (1 doubled-down)
CAC viabilityPayback <12 months; LTV/CAC >3 (David Skok)
Channel-fit-by-ICPBuyer presence / Buyer attention / Decision context, 1–5 each; sum ≥8 to qualify
Compounding vs. linearCompounding: SEO, content, community. Linear: outbound, paid. Run 1 of each at every stage
Stage rule1–3 channels drive 80% of acquisition at any stage

Procedure

  1. Brainstorm outer ring (all 19). Force consideration of every channel. 1-line annotation each. See ${HERMES_SKILL_DIR}/references/19-channels.md.
  2. Apply hard filters. Cut on CAC math / motion fit / stage fit / capital / time constraint. Survivors: 6–10.
  3. Score channel-fit-by-ICP. 1–5 on buyer presence, attention, decision context. Cut anything <8. Survivors: 4–7. See ${HERMES_SKILL_DIR}/references/channel-fit-matrix.md.
  4. Pick middle ring (3 channels). Likely-best + alternative + wildcard. Force ≥1 compounding + ≥1 linear.
  5. Design experiments per channel. Hypothesis / budget / duration / success / kill / owner / tools. See ${HERMES_SKILL_DIR}/references/experiment-template.md.
  6. CAC/LTV viability per channel. Cost per lead × lead-to-close → CAC. Payback = CAC / monthly ACV. Kill channels failing math.
  7. Allocate founder time + budget. Time as resource. Budget reserves 20–30% for tests.
  8. Build Bullseye plan. Outer / middle / inner (TBD post-results).
  9. Stage graduation plan. At next ARR milestone, which channels get added/swapped?
  10. Kill / scale / iterate criteria. Specific, measurable, time-bound per channel.

Pitfalls

  • Channel-of-the-month — chasing hype without ICP-fit math
  • "Channel that worked at last company" is hypothesis, not answer
  • Over-investing in compounding pre-PMF — SEO at 0 customers wastes capital
  • Cutting compounding too early — SEO/content take 6–12 months; killing at week 8 is the most common mistake
  • No kill criteria — channels quietly underperform for 6+ months and drain budget
  • Spreading thin — 5 mediocre channels < 2 great ones
  • All-linear mix — outbound + paid + ads = no compounding base

Verification

  1. All 19 channels considered and 1-line annotated
  2. 3 channels in middle ring with explicit experiment design
  3. CAC/LTV checked per top-3 channel
  4. Kill/scale/iterate criteria per channel
  5. ≥1 compounding + ≥1 linear in the mix
  6. Stage-graduation plan covers next 2 stages

Legend — Channel-Fit Score

  • [H] High — ICP regularly converts on this channel per evidence
  • [M] Medium — plausible fit, untested
  • [L] Low — poor demographic or behavioral match

Output Format

  • Sections required: Channel Matrix, Sources, Assumptions to Validate
  • Tables / fields:
    • Channel Matrix columns = Channel | Fit [H/M/L] | Estimated CAC [Sn] | Audience Reach [Sn] | Effort | Recommendation
  • Length target: 600–1,000 words
  • File type: markdown
  • Mandatory closing sections: Verification Notes, Sources, Assumptions to Validate, Next Step

Files bundled with it

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Other skills for the same job

Different authors, same problem. Matched on the words in the skill name, across every library in the catalogue except this one.

Need help setting it up?

This page tells you what channel-strategy does and what it needs. Cheetah builds the agent setup it runs inside: data, CRM, sequencing and the guardrails.

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