Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add geledek/enterprise-ai-transformation-skills/plugin install enterprise-ai-transformation-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/geledek/enterprise-ai-transformation-skills/general-maturity-assessment)<a href="https://agentmods.dev/skills/geledek/enterprise-ai-transformation-skills/general-maturity-assessment"><img src="https://agentmods.dev/badge/skills/geledek/enterprise-ai-transformation-skills/general-maturity-assessment/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/geledek/enterprise-ai-transformation-skills/general-maturity-assessment"><img src="https://agentmods.dev/badge/skills/geledek/enterprise-ai-transformation-skills/general-maturity-assessment.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 | $0.00157 | $0.01983 |
| Opus 5 | $0.00078 | $0.00992 |
| Sonnet 5 | $0.00031 | $0.00397 |
| Haiku 4.5 | $0.00016 | $0.00198 |
Grade A, and why
general-maturity-assessment 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 12d 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
General — AI Maturity Assessment
Plot the organization on the AI maturity curve. Identify the binding constraint. Build the roadmap to the next stage.
Two complementary frameworks: MIT CISR's four-stage sequential model (where are we, and what is next?) + Accenture's Foundation × Differentiation 2×2 (what is the binding constraint that's keeping us here?). Use both — they answer different questions.
Output contract (stable): MIT CISR stage placement (Stage 1 / Stage 2 / Stage 3 / Stage 4) plus Accenture archetype, with named next-stage actions.
Part 1: MIT CISR Stage Placement
Four stages, empirically associated with financial performance. Stages 1–2 = below-industry performance. Stages 3–4 = above-industry performance. The Stage 2 → Stage 3 transition is the most important threshold. (Consult mit-cisr-4-stages.md)
Stage diagnostics — answer each with evidence:
Stage 1 signals (Experiment and Prepare, 28% of firms):
- AI literacy program in place for board and senior leadership
- Acceptable-use policy for AI exists and is enforced
- Data accessibility initiative underway
- Individual AI experiments happening but no tracked, value-attributed pilots
- NOT yet: systematic pilots, APIs sharing data cross-silo, shared platform
Stage 2 signals (Build Pilots and Capabilities, 34% of firms):
- Tracked pilots with named business cases and measured value
- Data APIs connecting some silos
- LLMs in use to augment work in at least one function
- Internal storytelling about pilot learnings happening
- NOT yet: enterprise-wide platform; reusable models; test-and-learn as default; cross-function value
Stage 3 signals (Develop AI Ways of Working, 31% of firms):
- Shared AI platform with reusable services
- Business dashboards showing AI performance and value
- Test-and-learn is the default operating mode across functions
- Foundation models and SLMs in systematic use
- AI value visible and attributed across the organization
What ships with it
1 file 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.
- 12d ago First seen · 161 lines · 157 tokens per session scan A fd3066824f9c
general-maturity-assessment is a skill published in the GitHub repository geledek/enterprise-ai-transformation-skills (9 stars, last pushed 2mo ago), licensed MIT. It adds 157 tokens to every session and 1,983 once invoked, about $0.0008 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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