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 deciqAI/knowledge-skills --skill discovery-call-spingit clone --depth 1 https://github.com/deciqAI/knowledge-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/deciqai/knowledge-skills/discovery-call-spin)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/discovery-call-spin"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/discovery-call-spin/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/discovery-call-spin"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/discovery-call-spin.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 | $0.00075 | $0.00647 |
| Opus 5 | $0.00037 | $0.00324 |
| Sonnet 5 | $0.00015 | $0.00129 |
| Haiku 4.5 | $0.00007 | $0.00065 |
Grade A, and why
discovery-call-spin 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discovery Calls with SPIN — Let the Buyer Sell Themselves
Overview
SPIN Selling (Neil Rackham, from large-sale research) structures a discovery call around four question types in order — Situation, Problem, Implication, Need-payoff — so the buyer articulates the cost of their problem and the value of solving it, rather than being pitched. Implication questions (what the problem costs) are the ones that move complex deals. Talking less and questioning better outperforms feature-dumping.
The Process
- Situation (briefly) — enough context to be relevant; don't interrogate on facts you could research. Gate: too many situation questions bore the buyer — keep them minimal.
- Problem — surface real difficulties/dissatisfactions ("where does the current approach break down?").
- Implication — quantify the cost/ripple of that problem ("what does that delay cost per month? who else does it hurt?"). This is where urgency is built.
- Need-payoff — let them state the value of a solution ("if that were solved, what would it be worth?").
- Only then map your capability to their stated need — solve, don't pitch.
- Confirm next step / advance. Gate: no agreed next action = the call didn't progress the deal.
When to Use
- Consultative / considered-purchase sales
- Demos that show features but don't create urgency
- Qualifying whether pain is worth the buyer's spend
Applying It Well
- Talk <40%; the buyer should voice the pain and the payoff.
- Implication questions create urgency without pressure — invest there.
- Research situation facts beforehand; spend live time on problem/implication.
Red Flags
- Jumping to demo before implications are felt.
- Feature-dumping when the buyer hasn't quantified pain.
- Ending with "I'll follow up" instead of a scheduled advance.
Verification
- Situation kept minimal; researched in advance
- Problems surfaced in the buyer's words
- Implications quantified (cost of inaction)
- Buyer stated the payoff; concrete next step set
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 · 44 lines · 75 tokens per session scan A 0b5aadf658f2
discovery-call-spin is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 7d ago), licensed MIT. It adds 75 tokens to every session and 647 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 2026-08-31.
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