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 davekindl/skills --skill business-evolution-auditgit clone --depth 1 https://github.com/davekindl/skillsWrote 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/davekindl/skills/business-evolution-audit)<a href="https://agentmods.dev/skills/davekindl/skills/business-evolution-audit"><img src="https://agentmods.dev/badge/skills/davekindl/skills/business-evolution-audit/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/davekindl/skills/business-evolution-audit"><img src="https://agentmods.dev/badge/skills/davekindl/skills/business-evolution-audit.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 | $0.00139 | $0.01999 |
| Opus 5 | $0.00069 | $0.01000 |
| Sonnet 5 | $0.00028 | $0.00400 |
| Haiku 4.5 | $0.00014 | $0.00200 |
Grade A, and why
business-evolution-audit 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BUSINESS EVOLUTION AUDIT
Proactive audit. Demonstrated expertise. Revenue-backed roadmap. The email doesn't say "hire me" -- it says "I already found what you're leaving on the table."
Shared Infrastructure
- Persuasion principles: Read
references/persuasion-hooks.md(included in this skill's references/) - Sibling skills leveraged: the-inspector, seo-content-engine, deep-interrogation, gpt-image-2-techniques, grand-slam-offer
How It Works
5 sub-skills orchestrated by this master file. Steps 1-2 run in parallel, 3-5 are sequential.
INPUT: target URL + optional industry hint
│
┌────┴────┬───────────┐
▼ ▼ ▼ (parallel)
EVALUATE BENCHMARK UNIQUENESS
│ │ │
└────┬────┴───────────┘
▼
PLAN
│
┌────┴────┐
▼ ▼ (parallel)
TEASER PRICE
│ │
└────┬────┘
▼
COMPILE + HUMAN REVIEW
Input
Required: target URL (e.g., "ingatlan.com")
Optional: industry hint (e.g., "real-estate-portal")
Optional: output mode — "teaser-only" | "snapshot" | "full-audit"
Optional: language — "hu" | "en" (default: detect from target site)
If no industry hint, auto-detect from site content during EVALUATE.
Orchestration
Step 1+2: EVALUATE + BENCHMARK (parallel)
Read and invoke:
skills/evaluate.mdwith the target URL →site_health.json+sentiment.json+technical_audit.jsonskills/benchmark.mdwith the target URL + industry →competitor_matrix.json
These have NO dependencies on each other. Run via parallel Agent dispatch.
Step 2b: UNIQUENESS (parallel with 1+2)
Invoke the ai-uniqueness-test skill on the target (named competitors from BENCHMARK, JTBD situation-queries from the niche) → uniqueness_card.json + an HTML Uniqueness Card. This is the SELECTION axis — whether AI sees the target as a category-of-one or a swappable commodity — the differentiator no competing GEO/AEO tool measures. Two-mode (bare + grounded), local-Claude-compliant. The recommendation probe in EVALUATE measures presence (does AI name you); this measures substitutability (when AI picks, are you singular or swappable). Both feed PLAN.
What ships with it
11 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.
- references/geo-checklist.md 3.0 KB
- references/industry-templates/real-estate-portal.md 3.5 KB
- references/persuasion-hooks.md 3.8 KB
- references/pricing-guide.md 2.1 KB
- references/scoring-rubrics.md 2.5 KB
- skills/benchmark.md 3.7 KB
- skills/evaluate-legacy-playwright.md 4.2 KB
- skills/evaluate.md 24 KB
- skills/plan.md 5.4 KB
- skills/price.md 3.5 KB
- skills/teaser.md 4.7 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.
- 9d ago First seen · 162 lines · 139 tokens per session scan A a1f1fee31d08
business-evolution-audit is a skill published in the GitHub repository davekindl/skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 139 tokens to every session and 1,999 once invoked, about $0.0007 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 2026-08-31.
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