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Get Started Free →Use when the user asks to "track competitor influencer marketing", "see who my rivals partner with", or "benchmark my influencer program"; produces a competitor partnership roster, campaign and content-strategy breakdown, performance estimates, and a gap/opportunity list. Not for finding your own new creators — use influencer-discovery.
.claude/skills/aiskillstore-competitor-tracker/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 46% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 50% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 38% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 19% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 104% | 0% |
Monitor and analyze competitors' influencer marketing: who they partner with, what campaigns they run, how they structure collaborations, and what results they appear to achieve.
Shortest invocation:
Monitor [competitor name]'s influencer marketing activitiesCompare a set of rivals and surface gaps:
Compare influencer strategies across [competitor 1], [competitor 2], and [competitor 3], then show me which influencers they're missing in [category]memory/influencer/competitor-tracker/YYYY-MM-DD-<topic>.md (partnership roster, campaign analysis, content-strategy review, performance estimates, side-by-side comparison, opportunity list).memory/hot-cache.md. Competitor-partner and exclusivity flags for creators already on the roster go as one-line updates to memory/events/creators.ndjson via an authorized operation: propose request to registry-events.py for creator-registry to reconcile.> Emit the standard shape from skill-contract.md §Handoff Summary Format.
This family is Tier 1 — it works with no live integrations. Ask the user for the competitor set, the platforms, and any creator handles they already know, then build the analysis from public posts and stated estimates.
Where a tool could speed things up, use ~~ connector placeholders:
~~influencer database — pull a competitor's known partner roster and tier mix.~~social platform analytics — estimate reach, engagement rate, and post cadence per creator.~~CRM — cross-check whether a former competitor partner has already touched your pipeline.Keyless news read on rivals: python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/gdelt.py" '"<competitor>"' --days 30 lists a rival's global news coverage with no key — campaign launches, partnership announcements, PR pushes — Measured from GDELT's news index (news media only, not social posts; ≥5s between calls). See scripts/connectors/README.md.
Rival-partner channel watch (free key / keyless): python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/youtube.py" channel <partner-handle> reads a competitor partner's real subscriber/view counts (free YOUTUBE_API_KEY), and every YouTube channel also has a keyless RSS feed — https://www.youtube.com/feeds/videos.xml?channel_id=UC… piped into rss_monitor.py — for tracking partner posting cadence and spotting a burst of sponsored content without any API at all.
Label every estimate as an estimate. See CONNECTORS.md for the keyless/free recipe per category.
Each step has a fill-in template in references/templates.md.
User: "Track the influencer marketing activities of Glossier, Fenty Beauty, and Rare Beauty"
Output: Competitor analysis showing Glossier's UGC-heavy approach, Fenty's diverse creator network, Rare Beauty's mental health-focused partnerships, with identified gaps and ranked opportunities. Full invocation patterns, "what this skill does", and tips for success live in references/templates.md.
~~ connector category.Termination note: keep a visited-set of skills invoked this session. If the next skill has already run this session, stop and report the chain complete instead of re-invoking. Max chain depth is 3 hops.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 26,109 | 43,691 | +67% | 1 | 1 | 0% | 3,790 | 7,756 | +105% | 0 | 0 | — |
case-02 | fail→pass | 23,059 | 21,445 | -7% | 1 | 1 | 0% | 3,492 | 5,082 | +46% | 0 | 0 | — |
case-03 | fail→pass | 22,663 | 20,954 | -8% | 1 | 1 | 0% | 3,366 | 5,042 | +50% | 0 | 0 | — |
case-04 | fail→pass | 14,241 | 8,250 | -42% | 1 | 1 | 0% | 2,289 | 3,157 | +38% | 0 | 0 | — |
case-05 | fail→pass | 16,726 | 10,368 | -38% | 1 | 1 | 0% | 3,061 | 3,645 | +19% | 0 | 0 | — |
case-06 | fail→pass | 9,443 | 7,919 | -16% | 1 | 1 | 0% | 1,585 | 3,237 | +104% | 0 | 0 | — |
case-07 | fail→pass | 16,234 | 20,505 | +26% | 1 | 1 | 0% | 2,355 | 4,876 | +107% | 0 | 0 | — |
case-08 | fail→pass | 15,877 | 23,541 | +48% | 1 | 1 | 0% | 2,404 | 5,675 | +136% | 0 | 0 | — |
case-09 | fail→fail | 10,543 | 4,505 | -57% | 1 | 1 | 0% | 1,557 | 2,585 | +66% | 0 | 0 | — |
case-10 | fail→fail | 11,550 | 3,732 | -68% | 1 | 1 | 0% | 1,632 | 2,276 | +39% | 0 | 0 | — |
case-11 | fail→pass | 21,000 | 25,102 | +20% | 1 | 1 | 0% | 2,758 | 5,438 | +97% | 0 | 0 | — |
case-12 | pass→pass | 7,069 | 2,306 | -67% | 1 | 1 | 0% | 1,081 | 2,116 | +96% | 0 | 0 | — |
case-13 | pass→pass | 17,621 | 12,558 | -29% | 1 | 1 | 0% | 2,648 | 3,829 | +45% | 0 | 0 | — |
case-14 | fail→fail | 13,702 | 7,749 | -43% | 1 | 1 | 0% | 2,145 | 2,940 | +37% | 0 | 0 | — |
case-15 | fail→pass | 18,610 | 15,945 | -14% | 1 | 1 | 0% | 2,678 | 4,083 | +52% | 0 | 0 | — |
case-16 | fail→fail | 18,250 | 28,792 | +58% | 1 | 1 | 0% | 2,553 | 5,387 | +111% | 0 | 0 | — |
case-17 | fail→fail | 10,655 | 5,712 | -46% | 1 | 1 | 0% | 1,604 | 2,681 | +67% | 0 | 0 | — |
case-18 | fail→pass | 15,617 | 5,425 | -65% | 1 | 1 | 0% | 2,829 | 2,686 | -5% | 0 | 0 | — |
case-19 | fail→pass | 13,985 | 19,307 | +38% | 1 | 1 | 0% | 2,122 | 4,954 | +133% | 0 | 0 | — |
case-20 | pass→pass | 18,525 | 21,133 | +14% | 1 | 1 | 0% | 3,186 | 5,468 | +72% | 0 | 0 | — |
case-21 | pass→pass | 10,868 | 13,279 | +22% | 1 | 1 | 0% | 1,627 | 3,877 | +138% | 0 | 0 | — |
case-22 | pass→pass | 11,502 | 10,141 | -12% | 1 | 1 | 0% | 1,680 | 3,327 | +98% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +50 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.