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 product-on-purpose/thinking-framework-skills --skill think-interest-based-negotiationgit clone --depth 1 https://github.com/product-on-purpose/thinking-framework-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/product-on-purpose/thinking-framework-skills/think-interest-based-negotiation)<a href="https://agentmods.dev/skills/product-on-purpose/thinking-framework-skills/think-interest-based-negotiation"><img src="https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-interest-based-negotiation/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/product-on-purpose/thinking-framework-skills/think-interest-based-negotiation"><img src="https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-interest-based-negotiation.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 | $0.00142 | $0.02257 |
| Opus 5 | $0.00071 | $0.01128 |
| Sonnet 5 | $0.00028 | $0.00451 |
| Haiku 4.5 | $0.00014 | $0.00226 |
Grade A, and why
think-interest-based-negotiation 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 11d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interest-Based Negotiation
Most negotiation prep fixes on positions - what each side says it wants - and then plans to fight position against position, splitting the difference at the end. Interest-based negotiation refuses that frame. It models the counterparty (the move no solo decision method makes): it surfaces the interests behind the positions on BOTH sides of the table, anchors the accept-or-walk decision on a named, valued best alternative away from the table rather than on hope or the opening offer, and creates value across differently-valued issues before dividing it. The durable move is not the five-element checklist. It is treating the deal as a structured decision against an explicit alternative, with the counterparty's interests and alternatives modeled, not assumed. The output is a negotiation preparation map: positions and interests for both parties, the best alternative and reservation point, the zone of possible agreement, options for mutual gain built from valuation differences, the legitimacy standards a division can appeal to, and the follow-through an agreement must carry. It is explicitly preparation deskwork - not a script for the live table.
This method consolidates three formulations as one: Fisher and Ury's principled negotiation (separate the people from the problem, interests not positions, options for mutual gain, objective criteria, the best alternative as power anchor); Raiffa's decision-analytic skeleton (reservation prices, the zone of possible agreement, the efficient frontier); and the Mutual Gains Approach (prepare, create value, distribute value, follow through - the follow-through adopted here as a map section). The mechanisms coincide; the brand vocabulary is set aside for the descriptive move.
When to Use
- Agreement is required from a party you do not control, and more than one issue is in play - salary packages (pay, start date, scope, remote terms), vendor and partnership contracts (price, term, service level, exclusivity), cross-team resource conflicts, licensing and acquisition terms, multi-party public disputes.
- A position fight has hardened and no one has checked whether the interests are actually opposed. This is the documented failure mode the interests step exists to attack.
- A consequential negotiation is upcoming and the discipline is worth it on its own: naming and valuing your best alternative converts "I need this deal" into a priced choice.
What ships with it
5 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.
- 11d ago First seen · 72 lines · 142 tokens per session scan A b4d445f82d24
think-interest-based-negotiation is a skill published in the GitHub repository product-on-purpose/thinking-framework-skills (15 stars, last pushed today), licensed Apache-2.0. It adds 142 tokens to every session and 2,257 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 2026-08-30.
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