Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/deciqAI/knowledge-skillsnpx agentmods add skills/deciqai/knowledge-skills/realtor-closing-experience-peak-endWrote 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/deciqai/knowledge-skills/realtor-closing-experience-peak-end)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/realtor-closing-experience-peak-end"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/realtor-closing-experience-peak-end/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/deciqai/knowledge-skills/realtor-closing-experience-peak-end"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/realtor-closing-experience-peak-end.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 | $0.00089 | $0.00706 |
| Opus 5 | $0.00044 | $0.00353 |
| Sonnet 5 | $0.00018 | $0.00141 |
| Haiku 4.5 | $0.00009 | $0.00071 |
Grade A, and why
realtor-closing-experience-peak-end 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Real Estate — Closing Experience (Peak-End) Design
Industry front door for peak-end-rule. Adds domain triggers, example, packs. Parent Process unchanged. Guidance, not professional advice. No legal, tax, financial or regulatory advice; verify anything jurisdiction- or rate-dependent against current authority. The professional who acts owns the decision.
Activate when: designing the client experience across a transaction; planning the closing/keys moment; deciding where to invest effort for referrals. Do NOT activate when: no relationship/referral objective.
Why this variant
The parent peak-end-rule says memory is dominated by the emotional peak and the end. Real estate referrals — an agent's cheapest growth — are bought by engineering a memorable peak (getting the offer accepted / keys day) and a strong end (post-close follow-through), not by uniform effort that fizzles at closing.
Domain inputs → the parent's Process
- Engineer the peak: the "your offer was accepted" / keys-in-hand moment — make it special and personal.
- Engineer the end: closing day + the days after (housewarming gift, utility/mover checklist done for them, a check-in) so the transaction ends on a high, not a paperwork slog.
- De-risk the low: inspection/financing scares — proactive communication so anxiety doesn't scar the memory.
Worked example
Agent works hard through contract, then goes quiet post-inspection; closing is a rushed signing, no follow-up. → Peak-end fix: celebrate the accepted-offer peak, make keys day an event, deliver a post-close concierge touch. Same effort, redistributed → the client remembers a high and refers.
Packs
- Solo agent: define the one peak moment + a closing/post-close ritual.
- Team: standardized "raving-fan" closing experience as a referral engine.
Red flags
- Effort front-loaded, closing treated as admin.
- Silence during the scary middle (inspection/financing).
- No post-close touch → no referral trigger.
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 · 45 lines · 89 tokens per session scan A b096c22ca46a
realtor-closing-experience-peak-end is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 89 tokens to every session and 706 once invoked, about $0.0004 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.
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