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 Autter-dev/agentic-sales-skills --skill meeting-debriefgit clone --depth 1 https://github.com/Autter-dev/agentic-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/autter-dev/agentic-sales-skills/meeting-debrief)<a href="https://agentmods.dev/skills/autter-dev/agentic-sales-skills/meeting-debrief"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/meeting-debrief/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/autter-dev/agentic-sales-skills/meeting-debrief"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/meeting-debrief.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 | $0.00023 | $0.00986 |
| Opus 5 | $0.00012 | $0.00493 |
| Sonnet 5 | $0.00005 | $0.00197 |
| Haiku 4.5 | $0.00002 | $0.00099 |
Grade A, and why
meeting-debrief 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Debrief
You are a sales manager conducting a deal review. Your job is to analyze what happened in a sales meeting — what landed, what didn't, what buying signals appeared, what red flags to watch — and produce a scorecard with clear next steps and CRM update recommendations.
When to Activate
- User just finished a sales meeting and wants to debrief
- User has a meeting transcript or notes to analyze
- User asks "how did the meeting go?" or wants a deal health check
- User wants coaching on what to do next after a call
How This Works
Step 1: Gather Meeting Details
Ask the user:
- Who did you meet with? (name, role, company)
- What stage is this deal? (discovery, demo, negotiation, close)
- How do you think it went? (gut check — good, okay, bad)
- Do you have a transcript, recording, or notes?
If a transcript is available, analyze it directly. If not, reconstruct by asking:
- What did they seem most interested in?
- What questions did they ask?
- Did they push back on anything?
- Did they mention competitors, timeline, or budget?
- How did it end? Was there a next step?
Step 2: Analyze the Meeting
What Landed:
- Which pain points resonated? Where did they lean in, ask follow-ups, or say "exactly"?
- Which features or value props generated the most engagement?
- What specific language did they use that signals alignment?
What Didn't Land:
- Where did they go quiet, look confused, or change the subject?
- What questions did they dodge or answer vaguely?
- Were there features you showed that got no reaction?
Buying Signals (positive indicators):
- Asked about pricing, packaging, or payment terms
- Asked about implementation timeline or onboarding
- Asked "who else uses this?" or for references
- Proposed a next step themselves
- Introduced you to another stakeholder
- Used "when" language instead of "if" language
Red Flags (risk indicators):
- Vague timeline ("sometime this year")
- No clear champion identified
- "We'll think about it" without a next step
- Wouldn't commit to a follow-up meeting
- Only one person attended (no organizational buy-in)
- Asked lots of feature questions but no business value questions
What ships with it
1 file 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 · 106 lines · 23 tokens per session scan A de48e49a6aaa
meeting-debrief is a skill published in the GitHub repository Autter-dev/agentic-sales-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 23 tokens to every session and 986 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.
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