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 peterod99/consultant-skills --skill delivery-model-selectiongit clone --depth 1 https://github.com/peterod99/consultant-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/peterod99/consultant-skills/delivery-model-selection)<a href="https://agentmods.dev/skills/peterod99/consultant-skills/delivery-model-selection"><img src="https://agentmods.dev/badge/skills/peterod99/consultant-skills/delivery-model-selection/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/peterod99/consultant-skills/delivery-model-selection"><img src="https://agentmods.dev/badge/skills/peterod99/consultant-skills/delivery-model-selection.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 | $0.01216 |
| Opus 5 | $0.00015 | $0.00608 |
| Sonnet 5 | $0.00006 | $0.00243 |
| Haiku 4.5 | $0.00003 | $0.00122 |
Grade A, and why
delivery-model-selection 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 — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delivery Model Selection
When to use
You're designing a new offer and need to decide how hands-on you'll be. Is this done-for-you (you deliver everything), done-with-you (you guide the client through the work), or DIY (they do the work with your framework)? And will you deliver in-person, virtual, or asynchronously? Your answer depends on client maturity, your time constraints, and your price ceiling.
The framework
- Assess client maturity and willingness: Done-for-you works when the client is resource-constrained, has no in-house expertise, or is buying the solution, not the education. Done-with-you works when the client wants to learn and has 5+ hours/month to participate. DIY works only for clients who have solved 60% of the problem and need the last 40%.
- Map your time commitment per delivery model: Done-for-you: high touch, 80% client conversations + execution. Done-with-you: medium touch, 50% teaching + 50% execution. DIY: low touch, 20% support + 80% self-service content. The model determines your price ceiling and how many clients you can carry at once.
- Choose the time/location axis independently: In-person (you travel) adds scarcity premium (20–30% price bump) but limits volume (you're booked out in weeks). Virtual (video calls) is the default; async (Slack + recordings) is cheapest to deliver but requires client self-direction. Match to offer tier: $50K offer = in-person, $10K = virtual, $2K = async.
- Validate against your positioning: If you position as a high-touch, premium advisor, done-for-you in-person earns the price. If you're positioned as an educator / framework provider, DIY or done-with-you virtual wins. Delivery model must reinforce your positioning. (A $50K offer with pure async delivery signals you don't care; clients reject it.)
- Run a soft test with early clients: Offer the same service in two delivery models and track NPS, completion rate, referrals, and revenue. Done-for-you might earn 30% more but require 50% more time. The math determines scale.
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 · 38 lines · 29 tokens per session scan A 80ccb1a90fc8
delivery-model-selection is a skill published in the GitHub repository peterod99/consultant-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 29 tokens to every session and 1,216 once invoked, about $0.0001 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.
Other skills, from other repositories
strategy-consulting-visualization
Use when turning any content into clear, professional visualizations - board slides, reports, proposals, research summaries, training materials, technical diagrams, infographics, process flows, timelines, benchmarks, waterfall charts, or data-backed visual specs for any audience.
mckinsey-market-research-deck
End-to-end playbook for producing a top-tier, McKinsey-style market-research deck (HTML page-turning presentation + print-ready PDF) for a brand or product category. Covers the research methodology (TAM/SAM/SOM bottom-up, Good/Better/Best framework, competitor profiling, customer pain points, unit economics, business…
mckinsey-deck
Turn any content into a top-tier McKinsey-style deck — a 1280×720 page-turning HTML presentation that also prints to a clean per-slide PDF. Use when the user wants a "McKinsey-style deck / presentation", a polished slide deck or PDF from notes/content, an executive/board/investor deck, or to "make slides / a deck / a…
setup
Interactive setup wizard that configures the GTM Engine for a new user. Collects company context, team info, ICP, personas, messaging, and signals, then generates all config and context files.
good-morning
Daily morning briefing that pulls calendar, tasks, pipeline, and outreach data into one view.
cold-email
Write cold outreach emails using signal-based, pain-first messaging. Improves itself over time.