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 runxhq/runx --skill organic-growthgit clone --depth 1 https://github.com/runxhq/runxWrote 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/runxhq/runx/organic-growth)<a href="https://agentmods.dev/skills/runxhq/runx/organic-growth"><img src="https://agentmods.dev/badge/skills/runxhq/runx/organic-growth/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/runxhq/runx/organic-growth"><img src="https://agentmods.dev/badge/skills/runxhq/runx/organic-growth.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00039 | $0.01400 |
| Opus 5 | $0.00019 | $0.00700 |
| Sonnet 5 | $0.00008 | $0.00280 |
| Haiku 4.5 | $0.00004 | $0.00140 |
Grade A, and why
organic-growth 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 7d 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Organic Growth
Use this skill when an operator needs to decide what to improve on a site for organic discovery: technical search health, content demand, landing-page performance, conversion quality, or the clarity and citeability that can help a page appear in answer engines.
The output is a decision packet, not a bag of SEO tips. It separates what the evidence shows from what the analyst infers, ranks the next actions by expected impact, confidence, and effort, and says how each action should be measured. No action is executed by this skill.
Evidence comes first
The default analyze runner accepts a bounded objective, the site, optional
business constraints, and any combination of:
- search-performance evidence, such as a sealed
google-search-consoleperformance packet; - analytics evidence, such as a sealed
google-analyticsreport packet; - site or market evidence with a SHA-256 source/content digest, source reference, kind, and bounded extracted summary.
Google is optional. The canonical workflow depends on evidence contracts, not a provider, connector, credential store, or hosted tenant. A local crawler, self-hosted analytics service, another search provider, third-party connector, or Runx-hosted connector can supply evidence when its packet has a stable digest and useful provenance. Connector ids, credential handles, URLs, and tenant configuration never belong in this skill.
The admission step rejects invalid packet schemas, failed validation, missing digests, and unbounded evidence. It gives the analysis agent the rows, metadata, caveats, and business context needed for judgment, capped to an explicit analysis view. The complete source packet remains bound by digest; the model must not pretend a bounded view is exhaustive.
Every material claim and recommended action must cite one or more admitted source
digests. Runx's native evidence verifier rejects invented references, changed
objective/site identity, empty claims, missing decision fields, and unsupported
external-effect claims. A failure becomes needs_more_evidence, not a polished
guess.
What ships with it
2 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.
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.
- 7d ago First seen · 143 lines · 39 tokens per session scan A 115d06eb9a64
organic-growth is a skill published in the GitHub repository runxhq/runx (84 stars, last pushed yesterday), licensed Apache-2.0. It adds 39 tokens to every session and 1,400 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
dd-risk-scoring
Calculate weighted risk scores from specialist agent reports. Use when synthesizing multiple due diligence reports into an overall investment risk assessment.
dd-synthesis
Synthesize findings from multiple specialist agents into a coherent investment recommendation. Use when combining reports from 9+ specialist agents into a single decision document.
dd-report-format
Standard output format for due diligence analysis reports. Use when producing your final analysis to ensure consistency across all specialist agents.
dd-sourcing
Document sources properly for due diligence reports. Use when citing any external data, ensuring full traceability and auditability of findings.
dd-verification
Verify claims in pitch decks and founder statements using multiple independent sources. Use when analyzing any claim about market size, traction, team background, or competitive positioning.
codew-release-qa-sweep
Use before claiming Codewhale release work is done: run the full gate sweep and list the manual QA targets.