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 Doris-Labs/sales-skills --skill deal-risk-reviewgit clone --depth 1 https://github.com/Doris-Labs/sales-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/doris-labs/sales-skills/deal-risk-review)<a href="https://agentmods.dev/skills/doris-labs/sales-skills/deal-risk-review"><img src="https://agentmods.dev/badge/skills/doris-labs/sales-skills/deal-risk-review/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/doris-labs/sales-skills/deal-risk-review"><img src="https://agentmods.dev/badge/skills/doris-labs/sales-skills/deal-risk-review.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 | $0.00073 | $0.01463 |
| Opus 5 | $0.00036 | $0.00732 |
| Sonnet 5 | $0.00015 | $0.00293 |
| Haiku 4.5 | $0.00007 | $0.00146 |
Grade A, and why
deal-risk-review 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deal Risk Review
Purpose
Take a single deal and produce an honest health verdict: which specific risks are present, how severe each is, what to do about each, and whether the deal is red, yellow, or green. The goal is to catch a slipping deal before the forecast call, not after it pushes.
Inputs
- The deal: account, stage, amount, close date
- Who's engaged (and who isn't) — champion, economic buyer, blockers
- Activity history: last touch, last meeting, momentum over the last 2–4 weeks
- What you're trying to advance and the next confirmed step (if any)
Method
Run every deal against a fixed risk taxonomy. Don't grade on vibes — for each risk, mark present/absent, score severity, and attach a mitigation. Then roll up to a verdict.
The seven risks (taxonomy):
| # | Risk | Present when… |
|---|---|---|
| 1 | Single-threaded | Only one contact engaged; no second relationship in the account |
| 2 | No economic buyer engaged | You've never met or confirmed who controls the budget |
| 3 | No confirmed next step | No future meeting/milestone on the calendar with a date |
| 4 | Stalled / aging | No meaningful two-way activity in 14+ days, or deal age >> sales cycle for its stage |
| 5 | Active competitor | A named competitor is in the eval and not neutralized |
| 6 | Close-date slipping | The close date has moved out one or more times |
| 7 | No quantified pain | Pain is acknowledged but not tied to a number (cost, time, revenue, risk) |
Score each present risk 1–3:
- 1 (minor) — present but contained; a clear, cheap action fixes it.
- 2 (material) — credibly threatens the close date or amount; needs a deliberate play.
- 3 (critical) — can kill the deal on its own; nothing else matters until it's addressed.
Mitigation per risk (one specific play each):
- Single-threaded → name a second stakeholder to reach this week; ask your champion for a warm intro to one peer or their boss.
- No economic buyer → propose an exec-aligned next step (ROI review, exec readout); use a "who else signs off?" question to surface them.
- No confirmed next step → before any call ends, book the next one on the calendar; if none exists now, send a calendar hold with an agenda today.
- Stalled / aging → send a pattern-interrupt (status of the business case, a deadline, or a permission-to-close-the-file email); if no response, downgrade forecast.
- Active competitor → run a differentiation play on the buyer's stated criteria; arm the champion with a battlecard; trap-set on where the competitor is weak.
- Close-date slipping → rebuild the mutual close plan backwards from a real compelling event; if there's no event, the date is fiction — re-date it honestly.
- No quantified pain → run a cost-of-inaction calc with the buyer; convert pain to $ / hours / risk so the business case survives procurement.
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 · 102 lines · 73 tokens per session scan A 5a94106bbf64
deal-risk-review is a skill published in the GitHub repository Doris-Labs/sales-skills (3 stars, last pushed 3mo ago), licensed MIT. It adds 73 tokens to every session and 1,463 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.
Other skills, from other repositories
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lynqu-card-studio
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lynqu-competitors
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lynqu-contacts
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lynqu-deal-desk
Price a Lynqu deal and draft the quote — browse the price book, put priced lines on a deal, then produce a draft quote for a human to send. Requires the Lynqu MCP server connected.