Account Research
explorium-ai/gtm-skills
Account research skill for Claude Code and Codex: generate a high-signal company intelligence brief including firmographics, technographics, funding history, hiring signals, business events, recent…
Use this skill on a monthly cadence to detect champions and heavy users of your paying customers who changed jobs, verify the move against live LinkedIn data, score the new company, and surface…
$ npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install swan-gtm/gtm-skills champion-move-detection --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/swan-gtm/gtm-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ariel-cohen/champion-move-detection .claude/skills/champion-move-detection && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "champion-move-detection" agent skill from https://github.com/swan-gtm/gtm-skills/tree/main/skills/ariel-cohen/champion-move-detection into .claude/skills/champion-move-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "champion-move-detection", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/swan-gtm/gtm-skills/tree/main/skills/ariel-cohen/champion-move-detectionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install swan-gtm/gtm-skills champion-move-detection --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/swan-gtm/gtm-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ariel-cohen/champion-move-detection .agents/skills/champion-move-detection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "champion-move-detection" agent skill from https://github.com/swan-gtm/gtm-skills/tree/main/skills/ariel-cohen/champion-move-detection into .agents/skills/champion-move-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "champion-move-detection", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install swan-gtm/gtm-skills champion-move-detection --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/swan-gtm/gtm-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ariel-cohen/champion-move-detection .cursor/skills/champion-move-detection && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "champion-move-detection" agent skill from https://github.com/swan-gtm/gtm-skills/tree/main/skills/ariel-cohen/champion-move-detection into .cursor/skills/champion-move-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "champion-move-detection", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/swan-gtm/gtm-skills.git --path skills/ariel-cohen/champion-move-detection--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install swan-gtm/gtm-skills champion-move-detection --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/swan-gtm/gtm-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ariel-cohen/champion-move-detection .gemini/skills/champion-move-detection && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "champion-move-detection" agent skill from https://github.com/swan-gtm/gtm-skills/tree/main/skills/ariel-cohen/champion-move-detection into .gemini/skills/champion-move-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "champion-move-detection", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install swan-gtm/gtm-skills champion-move-detectionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/swan-gtm/gtm-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ariel-cohen/champion-move-detection .github/skills/champion-move-detection && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "champion-move-detection" agent skill from https://github.com/swan-gtm/gtm-skills/tree/main/skills/ariel-cohen/champion-move-detection into .github/skills/champion-move-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "champion-move-detection", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install swan-gtm/gtm-skills champion-move-detection --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/swan-gtm/gtm-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ariel-cohen/champion-move-detection .opencode/skills/champion-move-detection && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "champion-move-detection" agent skill from https://github.com/swan-gtm/gtm-skills/tree/main/skills/ariel-cohen/champion-move-detection into .opencode/skills/champion-move-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "champion-move-detection", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
champion-move-detectionUse this skill on a monthly cadence to detect champions and heavy users of your paying customers who changed jobs, verify the move against live LinkedIn data, score the new company, and surface…
Champion Move Detection is an agent skill from swan-gtm/gtm-skills. Use this skill on a monthly cadence to detect champions and heavy users of your paying customers who changed jobs, verify the move against live LinkedIn data, score the new company, and surface qualifying moves as MQLs — while catching churn risk on the account they left. A known buyer bringing your product to their next company is one of the highest-converting signals in B2B; this skill turns it into a deterministic, deduped, monthly machine with hard guards against the classic failure modes (stale headlines…
Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/setup-customization-checklist.md`).
It sits in Sales & Support, covering Customer success. It works with LinkedIn. The repository describes itself as: Open, production-grade GTM skills for AI agents. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 67abd04. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Champion Move Detection loads about 5k tokens when it runs, and up to ~5.8k if it reads all its reference files. Until then it costs about 150 tokens; SKILL.md has 2,826 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from swan-gtm/gtm-skills at commit 67abd04, republished under its MIT licence (© swan-gtm). 2,826 words, ~4,974 tokens.
.claude/skills/champion-move-detection/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Once a month, detect champions and heavy users of your paying customers who changed jobs and moved to a new company. A known buyer bringing {{PRODUCT}} to their next company is one of your highest-conversion signals — score the new company and surface it as an MQL when it qualifies. Secondary purpose: catch churn risk on the account they left.
Replace every {{...}} before enabling. See the setup checklist for the full list.
{{PRODUCT}} — Your product's name{{CRM}} — Your CRM (e.g. HubSpot, Salesforce, Attio){{SCORING_SKILL}} — Your account-scoring skill/process; this skill feeds moves into it as a high-intent signal{{LINKEDIN_LOOKUP}} — Live LinkedIn profile lookup tool (e.g. an Apify profile-search actor). Must return the profile's full experience section{{MQL_OWNER}} — Who owns champion-move MQL tasks and alerts{{DIGEST_CHANNEL}} — Where the monthly digest posts{{COMPETITORS}} — Your direct competitors (moves into these are logged, never scored){{WATCHLIST_MAX}} — Max watched people per account (default: 5){{REFRESH_WINDOW}} — Days before an account's watchlist is rebuilt (default: 90){{USAGE_WINDOW}} — Lookback for "materially active" usage (default: 90 days){{SELF_SERVE_THRESHOLD}} — Company size/funding below which a move is future pipeline, not an MQL (default: <50 employees AND ≤$10M raised){{TIER_FLOOR}} — Minimum tier a confirmed champion move scores (default: one tier above your standard mid-tier — mirror of a closed-lost floor if you run one)Run across BOTH:
champion-move AND holding an active [CHAMPION WATCHLIST] entry marked carried-forward (see Phase 3.C). These are NOT customers; they are companies a proven serial champion moved into, tracked so you catch the person's NEXT move. A serial champion is your highest-value signal — never drop them because their current employer isn't a customer.Expect the first full run to be slow and partial — it builds a watchlist for every customer from messy records. Report coverage gaps honestly in the digest rather than skipping silently; coverage compounds monthly.
Memory updates, state summaries, the champion-move tag, MQL stage moves, and alerts — nothing else. Never send outreach from this skill. It recommends; humans send.
For each Closed Won account, maintain a watchlist of up to {{WATCHLIST_MAX}} people, persisted in the account's memory under the header [CHAMPION WATCHLIST]. If the header exists and was refreshed within the last {{REFRESH_WINDOW}} days, reuse it and go straight to Phase 2 for that account.
A person qualifies via either bar:
How to identify heavy users. Use per-person usage attribution from your product's analytics (individual events/credits/seats-activity by user). Org-level totals cannot attribute usage to a person — never use them for this. Treat self-declared titles in product data as a persona hint; confirm seniority via {{CRM}}/LinkedIn, never as ground truth.
Watchlist rules (do not soften):
Persist in account memory:
[CHAMPION WATCHLIST] — refreshed [date]
- [Name] | [title] | [email] | [LinkedIn URL] | [champion / economic buyer / heavy user: ~N usage/{{USAGE_WINDOW}}] | last verified [date]Skip guard (dedup — check FIRST). Skip any watchlist entry already marked MOVED → [company], processed [date] (see Phase 3.A). That move already fired once; re-detecting it would re-surface the same MQL. These entries are historical records, not active watch targets. Only the person's CURRENT-employer entry (active, or carried-forward) is live for detection.
For every ACTIVE watchlist person, verify current employment against live LinkedIn via {{LINKEDIN_LOOKUP}}.
Live lookup is the authoritative source for the move-check — always run it for every active watchlist person. You are detecting recent job changes, and cached enrichment lags exactly where recent moves happen — a champion who changed jobs last month is precisely the case cached data gets wrong. So:
Batch lookups aggressively — this is lookup work, not deep research; delegate across sub-agents when the watchlist is large.
Verification rules (do not skip):
dual-role — and soften all churn language on the old account (they have not left; they have added a role).Classify each person: STILL (update "last verified" date) / MOVED (record new company, new title, move date if shown) / UNCERTAIN.
Ignore moves where the new company is another existing customer — that is an internal reshuffle, not a new-logo signal. Note it in the old account's memory but do not create an MQL.
When this skill runs as a delegated batch sub-agent (e.g. a monthly sweep fanned out across many accounts), execute Phases 1–2 ONLY. Do NOT execute Phase 3: no stage moves, no tier tags, no {{CRM}} writes, no channel posts, and no tasks of any kind.
Task ownership (routing). Every champion-move task or alert this phase produces is assigned to {{MQL_OWNER}}. The prior-relationship owner is not an automatic sender — surface them as a recommendation inside the task (e.g. "consider having [prior deal owner] send — they owned the relationship at [Old Account]"). {{MQL_OWNER}} decides who sends.
A. The old account (company losing a champion):
[CHAMPION DEPARTED] [date] — [Name] ([title]) left for [New Company] ([new title]). Was: [qualification reason].[CHAMPION WATCHLIST] line on this account to MOVED → [New Company], processed [date]. This entry is now a historical record — Phase 2's skip guard will never re-detect it, so the same move can only ever fire ONE MQL. Do not delete it; the record is what makes the run idempotent month over month.[CHAMPION DEPARTED] entries), flag a critical churn risk prominently in the digest.B. The new company:
Champion-qualification gate (run BEFORE everything else in Phase 3.B). The champion-move machinery — tier floor, MQL, champion-move tag — only applies to a person who actually realized value at the origin company. A move is NOT a champion move just because the person was a registered user or a named deal contact. Confirm BOTH:
If EITHER check fails → STOP: no tier floor, no MQL, no champion-move tag, no scoring run. Log the move to both companies' memory and, only if the person is GTM-relevant and the new company is a plausible ICP fit, post a soft FYI to the digest as a potential future warm intro from the prior deal owner — never a sales motion, never an MQL. Still carry the person forward per Phase 3.C (trajectory tracking is independent of this gate). Only when BOTH checks pass does the move proceed to scoring with the tier floor.
Competitor / never-prospect check FIRST. If the new company is one of {{COMPETITORS}} (or any direct competitor per your competitive knowledge) → log to memory only. No scoring, no outreach, no MQL. Also respect any standing never-prospect entries in org memory.
Verify the new company's employee count and funding with real sources (LinkedIn company page; enrichment for funding). Never guess funding — routing hinges on it. If funding cannot be sourced and employee count is near {{SELF_SERVE_THRESHOLD}}, classify routing as NEEDS-REVIEW in the digest instead of deciding.
Score the new company — this trigger behaves like every other signal-driven trigger. Load and run {{SCORING_SKILL}} in full, feeding the champion move in as the triggering high-intent, first-party signal with relationship context. The scoring skill then owns everything downstream: gates, tier, MQL routing, buying-committee enrichment, alerts, and any outreach — exactly as it does for a website visit or a hand-raise. Do NOT hand-craft a separate outreach motion here.
When scoring lands at or above {{TIER_FLOOR}} with no gate fired, it produces an MQL through its normal flow. This skill contributes only its provenance markers:
champion-move tag to the new company.Multiple movers to the SAME destination = ONE stronger signal, scored once. Never fire several MQLs for one company.
Prepend to the new company's memory: [CHAMPION ARRIVED] [date] — [Name] joined as [new title]. Ex-[Old Account] ([qualification reason]). Scored [tier]. MQL: [yes/no + why].
C. Carry the champion forward (track serial movers forever):
A proven mover — someone who already carried {{PRODUCT}} from one company to another — is your highest-value person to keep watching. Their NEXT move is a hotter signal than this one, not colder. The champion travels with the person, not the account.
[CHAMPION WATCHLIST] as a live, carried-forward entry:
- [Name] | [new title] | [email if known] | [LinkedIn URL] | carried-forward: ex-[Old Company] ([original qualification reason]) | last verified [date]
This entry is ACTIVE for detection — next month Phase 2 verifies them against the new company and detects their move to a third company, firing a fresh MQL there. The chain continues indefinitely across every future move.champion-move tag on the new company (from B.4) + the active carried-forward watchlist entry are what put this company into next month's scan set. Both are required.carried-forward entries — those are tracked people, not native champions of the account, and would never be rediscovered by a {{CRM}}/usage scan. Preserve all carried-forward and MOVED → processed entries across rebuilds; only refresh the natively-sourced lines.End every run with ONE summary message to {{DIGEST_CHANNEL}} containing: accounts scanned, watchlist size, moves confirmed (with tiers + MQL status), FYI-routed moves (self-serve/gated), UNCERTAIN people needing human review, churn-risk flags (compound departures first), NEEDS-REVIEW routing calls (unsourced funding), and coverage gaps (accounts with no identifiable champion; customer domains with no matching workspace).
A monthly run reads like a machine, not a hunch: every active watchlist person got a live LinkedIn check; every MOVED classification survived the experience-section read, the affirmative-evidence bar, and the wrong-person guard; warm familiarity never got promoted to champion; a mover into a competitor or a tiny startup produced a memory note and an FYI, not an MQL; one company with three arriving champions fired exactly one scoring run; the old accounts got churn flags (critical when compound); serial movers stayed on watch at their new company; and the digest let a human review every UNCERTAIN instead of the machine guessing. The failure modes this skill exists to prevent: a same-name stranger becoming a hot MQL, a stale headline hiding a move, the same move firing MQLs two months running, and a free-trial signup being treated like an advocate.
© swan-gtm, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in skills/ariel-cohen/champion-move-detection of swan-gtm/gtm-skills.
Open the folder on GitHubat commit 67abd04
Champion Move Detection next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Champion Move Detection this skillswan-gtm/gtm-skills | 172 | — | ~5k | Automated safety check: Pass | MIT | |
| Account Researchexplorium-ai/gtm-skills | 185 | — | ~2.8k | Automated safety check: Pass | MIT | |
| Prospectingcoreyhaines31/marketingskills | 54k | — | ~5k | Automated safety check: Pass | MIT | |
| Sales OsromangojiberryAI/gojiberryai-sales-os | 139 | — | ~2k | Automated safety check: Pass | MIT | |
| Lead Generation Research GuideRightNow-AI/openfang | 18k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Cold Outreach Personalizeraiskilloftheweek/claude-ai-skill-of-the-week | 149 | — | ~2.6k | Automated safety check: Pass | None |
explorium-ai/gtm-skills
Account research skill for Claude Code and Codex: generate a high-signal company intelligence brief including firmographics, technographics, funding history, hiring signals, business events, recent…
coreyhaines31/marketingskills
When the user wants to find, qualify, and build a list of prospects to reach out to, across B2B SaaS, general B2B, or local small businesses.
romangojiberryAI/gojiberryai-sales-os
A complete outbound sales department in one skill. An agent skill from romangojiberryAI/gojiberryai-sales-os.
RightNow-AI/openfang
Reference knowledge for AI lead generation: building an ideal customer profile, researching prospects on the web, enriching lead records and finding email formats.
aiskilloftheweek/claude-ai-skill-of-the-week
Generates hyper-personalized cold outreach messages (email, LinkedIn DM, connection request) from raw prospect research.
mohitagw15856/pm-claude-skills
Build a customer health scorecard for a specific account. An agent skill from mohitagw15856/pm-claude-skills.
swan-gtm/gtm-skills
Annual and quarterly revenue plan construction, top-down vs bottoms-up reconciliation, plan versioning, stretch goal handling, and FP&A-RevOps collaboration for B2B revenue teams.
swan-gtm/gtm-skills
A skill your agent uses when setting up AI-powered personalization, building Clay or lemlist workflows, or automating prospect research — 6 AI personalization prompts (lemlist style) plus 2 email…
swan-gtm/gtm-skills
A skill your agent uses when a list of people already exists and someone needs to know who on it is worth contacting — event or webinar attendees, registrants, a prospecting export, a CRM segment, a…
swan-gtm/gtm-skills
A skill your agent uses when you need to know what people are saying about a brand across the web and social — "monitor brand mentions", "what are people saying about [brand] this week", "run a…
swan-gtm/gtm-skills
Use this skill before staging a prospect and before drafting any first touch, when a segment has gone silent, and when deciding whether an account is genuinely cold.
swan-gtm/gtm-skills
A skill your agent uses when building enrichment workflows, setting up Clay tables, or maximizing data quality — the complete 9-step Clay enrichment workflow for 90%+ data coverage plus 58 Clay…
Works with
Categories
Use this skill on a monthly cadence to detect champions and heavy users of your paying customers who changed jobs, verify the move against live LinkedIn data, score the new company, and surface…. Champion Move Detection is an agent skill from swan-gtm/gtm-skills. Use this skill on a monthly cadence to detect champions and heavy users of your paying customers who changed jobs, verify the move against live LinkedIn data, score the new company, and surface qualifying moves as MQLs — while catching churn risk on the account they left.
Champion Move Detection fits situations like: tasks that involve Customer success.
Run `npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a claude-code`. Or copy the skill folder (skills/ariel-cohen/champion-move-detection in swan-gtm/gtm-skills) into .claude/skills/champion-move-detection in your project. Claude Code loads it when a task matches its description.
Run `npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a codex`. Or copy the skill folder (skills/ariel-cohen/champion-move-detection in swan-gtm/gtm-skills) into .agents/skills/champion-move-detection in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add swan-gtm/gtm-skills --skill champion-move-detection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/champion-move-detection, .gemini/skills/champion-move-detection, .github/skills/champion-move-detection and .opencode/skills/champion-move-detection in your project.
SKILL.md names no scripts, command-line tools or credentials: Champion Move Detection is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Champion Move Detection is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 5k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 840 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Champion Move Detection: Account Research (explorium-ai/gtm-skills, 185 stars), Prospecting (coreyhaines31/marketingskills, 54k stars), Sales Os (romangojiberryAI/gojiberryai-sales-os, 139 stars) and Lead Generation Research Guide (RightNow-AI/openfang, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
swan-gtm (a GitHub organization) maintains it in swan-gtm/gtm-skills, which has 172 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on October 8, 2026.
Source: swan-gtm/gtm-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.