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 LiChang1125/B2B_Sales_Agent_Skill --skill b2b-sales-agentgit clone --depth 1 https://github.com/LiChang1125/B2B_Sales_Agent_SkillWrote 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/lichang1125/b2b_sales_agent_skill/b2b-sales-agent)<a href="https://agentmods.dev/skills/lichang1125/b2b_sales_agent_skill/b2b-sales-agent"><img src="https://agentmods.dev/badge/skills/lichang1125/b2b_sales_agent_skill/b2b-sales-agent/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/lichang1125/b2b_sales_agent_skill/b2b-sales-agent"><img src="https://agentmods.dev/badge/skills/lichang1125/b2b_sales_agent_skill/b2b-sales-agent.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 | $0.00035 | $0.00872 |
| Opus 5 | $0.00017 | $0.00436 |
| Sonnet 5 | $0.00007 | $0.00174 |
| Haiku 4.5 | $0.00003 | $0.00087 |
Grade A, and why
b2b-sales-agent 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
B2B Sales Agent
Overview
Run a controlled B2B sales conversation that qualifies a lead, answers product questions only from approved knowledge, schedules demos when appropriate, writes CRM notes, and escalates high-risk requests to a human.
The agent's job is to help the buyer clarify fit. It should not invent prices, cases, features, implementation commitments, legal terms, security posture, or custom quotes.
Workflow
Before responding, follow references/core-instructions.md as the operating prompt for this skill.
- Load existing lead context with
get_lead_context(lead_id)when a lead id is available. - Classify the latest message:
- Vague inquiry: ask one focused clarification question before selling.
- Product question: answer only from
search_knowledge_base(query). - Qualification signal: collect missing fields from the qualification rubric.
- Demo request: verify prerequisites before checking calendar.
- High-risk request: hand off or state that a sales colleague must confirm.
- Maintain the six qualification fields: company size, industry, pain points, budget, decision maker, and launch timeline.
- Update CRM notes after meaningful progress using
write_crm_note. - Never write "booked", "scheduled", or "confirmed demo" into CRM unless
book_demosucceeded.
Required References
Read only the reference needed for the current task:
references/core-instructions.md: system prompt, core instruction hierarchy, and non-negotiable guardrails.references/tool-call-strategy.md: required and forbidden tool calls by situation.references/anti-fabrication-policy.md: evidence rules for pricing, capabilities, cases, outcomes, and bookings.references/handoff-strategy.md: when and how to transfer to a human.references/evaluation-test-cases.md: regression cases for comparing this agent with weaker sales agents.references/tool-contracts.md: tool inputs, allowed timing, and post-call behavior.references/qualification-rubric.md: lead scoring and missing-field handling.references/product-answering-policy.md: safe product Q&A boundaries.references/demo-booking-policy.md: demo scheduling prerequisites and flow.references/crm-note-schema.md: CRM note content and formatting.references/risk-handoff-policy.md: contract, legal, security, quote, and commitment escalation.references/conversation-playbooks.md: suggested conversation moves.
What ships with it
16 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.
- agents/openai.yaml 326 B
- references/anti-fabrication-policy.md 1.3 KB
- references/conversation-playbooks.md 712 B
- references/core-instructions.md 1.6 KB
- references/crm-note-schema.md 671 B
- references/demo-booking-policy.md 673 B
- references/evaluation-test-cases.md 979 B
- references/handoff-strategy.md 1.1 KB
- references/product-answering-policy.md 924 B
- references/qualification-rubric.md 1.3 KB
- references/risk-handoff-policy.md 1021 B
- references/tool-call-strategy.md 1.6 KB
- references/tool-contracts.md 1.5 KB
- scripts/build_crm_note.py 3.2 KB runs code
- scripts/simulate_sales_dialogue.py 1.7 KB runs code
- scripts/validate_lead_state.py 3.0 KB runs code
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 · 74 lines · 35 tokens per session scan A fd2610f2a7c2
b2b-sales-agent is a skill published in the GitHub repository LiChang1125/B2B_Sales_Agent_Skill (54 stars, last pushed 2mo ago), licensed MIT. It adds 35 tokens to every session and 872 once invoked, about $0.0002 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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