Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add event4u-app/agent-config --skill funnel-analysisgit clone --depth 1 https://github.com/event4u-app/agent-configWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/event4u-app/agent-config/funnel-analysis)<a href="https://agentmods.dev/skills/event4u-app/agent-config/funnel-analysis"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/funnel-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/event4u-app/agent-config/funnel-analysis"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/funnel-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.01669 |
| Opus 5 | $0.00017 | $0.00834 |
| Sonnet 5 | $0.00007 | $0.00334 |
| Haiku 4.5 | $0.00003 | $0.00167 |
Grade A, and why
funnel-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
funnel-analysis
When to use
- Conversion to paid dropped and nobody knows which step broke.
- A new signup channel went live and you need to compare its funnel shape to the baseline.
- A board ask: "where does the money leak between landing page and paying customer?"
Do NOT use for ranking features, valuation, or OKR decomposition (see Related Skills). Funnel analysis is a diagnostic, not a roadmap.
Cognition cluster
- Mental model 16 — Leading vs. lagging indicators. Paid is
lagging; activation is leading; signup is upstream of both. A
funnel decision built on the lagging stage can only confirm the
miss; the leading stage names the binding fix. See
docs/contracts/mental-models.md§ 16. - Mental model 13 — Occam's razor. When a stage drops, the
simpler explanation usually wins: "acquisition mix shifted"
beats "users no longer understand the product." Pick the simpler
cause; it changes the move. See
mental-models.md§ 13. - Mental model 3 — Pareto (80/20). Drops are almost never
uniform across segments; ~20 % of the segment × stage cells carry
~80 % of the loss. Segment before treating the average as
actionable. See
mental-models.md§ 3. - Context-spine — product + customer-segment + funnel-stage.
Read the product slot for what activation can actually mean
in-product (the activation event must be shippable), the
customer-segment slot for which segments' switch-events the
funnel is built for, and the funnel-stage slot for the
position of each stage relative to the buying journey. See
context-spine.
Procedure
Step 0: Inspect
- Confirm the cognition cluster: this is conversion diagnosis, channel-agnostic. Paid social, organic, partner, and self-serve all share the same shape; only the inputs differ.
- Confirm event tracking exists for all 5 stages. If even one stage is inferred, the analysis is unreliable — flag and proceed under that caveat.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 134 lines · 35 tokens per session scan A bb2d8c546e5a
funnel-analysis is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 1,669 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
save-progress
Save current project task progress to local task state file for cross-session continuity. Use when the user asks to save progress, uses an equivalent localized trigger phrase, the session is interrupted, or the user wants to resume work later. Writes to .claude/project-task-state.json so next session can load it via…
meta-theory
MetaKim executable governance dispatcher. It classifies the run, loads only needed references, preserves foundational capabilities and runtime-native abilities, routes owner + weapon + dependency + runtime + OS + verification, and closes only with evidence, intent acceptance, and writeback decision.
same-set-reusable-flow-for-project-file-inventor
Reusable MetaKim file inventory classification flow. It helps separate durable sources, generated evidence, runtime mirrors, temporary state, and risky unknowns before cleanup or commit.
starreel-drama-production
Operating skill for any AI agent driving the StarReel short-drama production pipeline (script → rewrite → extract → portraits + sheets → storyboards → frames → video → voiceover → final cut) over MCP or REST. Covers the ordered workflow, the entry-point decision table (which channel each kind of customer material…
seedance-20
Generate and direct cinematic AI videos with Seedance 2.0 (ByteDance/Dreamina/Jimeng). Covers text-to-video, image-to-video, video-to-video, and reference-to-video workflows with @Tag asset references, multi-character scenes, audio design, and post-processing. Use when making AI video, writing Seedance prompts…
monorepo-management
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.