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 manishiitg/coding-agent-loop --skill funnel-conversion-intelligencegit clone --depth 1 https://github.com/manishiitg/coding-agent-loopWrote 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/manishiitg/coding-agent-loop/funnel-conversion-intelligence)<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/funnel-conversion-intelligence"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/funnel-conversion-intelligence/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/manishiitg/coding-agent-loop/funnel-conversion-intelligence"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/funnel-conversion-intelligence.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 | $0.00029 | $0.00771 |
| Opus 5.5 | $0.00012 | $0.00308 |
| Sonnet 5.5 | $0.00006 | $0.00154 |
| Haiku 4.5 | $0.00003 | $0.00077 |
Grade A, and why
funnel-conversion-intelligence 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 20d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Funnel and Conversion Intelligence
Outcome
Funnel Analyst reconciles eligible, signup, activated and paid accounts for a defined cohort. Growth Experiment Planner consumes the validated observation and proposes one bounded test. An observed rate change is not a causal explanation or an experiment result.
When to use
Use for a SaaS signup-to-paid question with authorized event and billing records. Campaign Signal covers campaign responses; Website Growth Loop covers site traffic. A new company can start with one complete baseline window and no trend.
Discovery and user direction
Builder inspects sources, event definitions, identity join, existing Crews and owner. It proposes distinct Funnel Analyst and Growth Experiment Planner Crews in chat. Selection creates no Crew, query, experiment or schedule.
Required inputs
Record product/tenant and eligible cohort, ordered stage versions, time zone, exclusions, identity and deduplication rules, event and paid-state sources, source freshness, comparison windows, minimum join coverage, owner, primary metric, guardrail and action policy. Consent is required before session replay; replay is optional.
Plan and AgentWorks tools
- Bind two Crew IDs and Workflow steps. Funnel Analyst reads scoped event and billing records, captures unique-user counts and source revisions, and saves
funnel-observation/v1at its step path. Runpython3 scripts/validate_handoff.py observation <observation.json>as a blocking step. - Growth Experiment Planner reads the validated artifact through a checked alias. It preserves cohort and metric IDs, states a falsifiable hypothesis, assignment unit, guardrail and pending sample calculation, then saves
funnel-experiment-plan/v1. Runpython3 scripts/validate_handoff.py plan <observation.json> <plan.json>before reporting. - Review the result and proposed test with the owner. A separate approved route must calculate power, launch a variant and later compare outcomes. No schedule or external write follows from this proposal.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/conversion-investigation.json 1.1 KB
- examples/funnel-baseline-first-plan.json 1.7 KB
- examples/funnel-baseline-first.json 2.3 KB
- examples/funnel-experiment-plan.json 1.6 KB
- examples/funnel-observation.json 2.5 KB
- examples/invalid-funnel-experiment-plan.json 1.1 KB
- playbook.json 5.4 KB
- references/conversion-intelligence-workflow.md 3.0 KB
- references/team-and-handoffs.md 2.9 KB
- scripts/test_validate_handoff.py 3.7 KB runs code
- scripts/validate_handoff.py 11 KB runs code
- SETUP.json 3.2 KB
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.
- 20d ago Changed · +2 lines · -22 tokens per session 3fe0fe6c2809
- 1mo ago First seen · 51 lines · 51 tokens per session scan A 076c1ebb5c75
funnel-conversion-intelligence is a skill published in the GitHub repository manishiitg/coding-agent-loop (13 stars, last pushed 19d ago), licensed MIT. It adds 29 tokens to every session and 771 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-15.
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