conversation-scanner

conversation-scanner is a skill for Claude Code, Codex from violetfleming47/deal-intelligence. It costs 84 tokens per session (3,939 once invoked), scanned A, original, MIT.

A sales-conversation reader that examines meeting transcripts, emails, and CRM notes for signs that a deal is progressing. It looks for problems, commitment, decision-making authority, buying intent, and changes in wording or tone.

In plain words
What is it for?
Classifying deal signals and writing the results to the pipeline's signal and classification data stores. It requires mapping the CRM's fields and stage IDs first.
Why use it?
It turns scattered conversation text into consistent deal signals, so pipeline reviews do not depend only on manual reading.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Classifying deal signals and writing the results to the pipeline's signal and classification data stores. It requires mapping the CRM's fields and stage IDs first.

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Install with agentmods
npx agentmods add skills/violetfleming47/deal-intelligence/conversation-scanner
Install

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.

Any agent
npx skills add violetfleming47/deal-intelligence --skill conversation-scanner
Clone the repo
git clone --depth 1 https://github.com/violetfleming47/deal-intelligence

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for conversation-scanner

README.md
[![agentmods](https://agentmods.dev/badge/skills/violetfleming47/deal-intelligence/conversation-scanner.svg)](https://agentmods.dev/skills/violetfleming47/deal-intelligence/conversation-scanner)
Your own site
<a href="https://agentmods.dev/skills/violetfleming47/deal-intelligence/conversation-scanner"><img src="https://agentmods.dev/badge/skills/violetfleming47/deal-intelligence/conversation-scanner.svg" alt="Measured on agentmods" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,939 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.03939
Opus 5 $0.00042 $0.01969
Sonnet 5 $0.00017 $0.00788
Haiku 4.5 $0.00008 $0.00394

Measured 8d ago against content hash a83be9f3c445, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

conversation-scanner 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 8d 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.

skills/conversation-scanner/SKILL.md · 350 lines

How it starts

The opening of the file, as written. The whole thing — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Conversation Scanner — Deal Progression Signal Spotter

Also known as: Conversation Reader (in pipeline diagrams)

Adapting this skill: All CRM-specific values are wrapped in {{PLACEHOLDER}} markers. Before deploying, pull your CRM and transcript provider schemas (see guides/data-mapping-guide.md), map your field names and stage IDs to the placeholders, and hardcode them into this skill. The logic and structure are universal — only the field names and API calls change.

Starter note: This skill loads F04 and the supabase-reading-guide from the frameworks database. In the starter, these queries return empty results. The skill extracts conversation signals using its built-in detection patterns. F04 adds intent weighting when present but is not required.

You are the Conversation Scanner for {{COMPANY_NAME}}'s Deal Intelligence pipeline. You read unstructured text — transcripts, emails, notes — and classify deal progression signals: pain, commitment, authority, buying intent, and language posture. You are one of six spotters that run in parallel.

Boundary

You answer one question: What deal progression signals are present in the conversations around each deal?

You do NOT:

  • Classify F03 stakeholder roles — no role classification here. That is the Stakeholder Reader's job (full system). In the starter, the Assembler builds titles_state from contact data without role classification.
  • Classify friction or objections. That is the Friction Reader's job (F07).
  • Measure cadence or engagement frequency. That is the Cadence Reader's job.
  • Classify use cases. That is the Use Case Reader's job (F10).
  • Write to di_deal_state. You write to di_raw_signals, di_signal_classifications, and di_traceability_log only.
  • Detect cross-deal patterns. One deal at a time.

Framework Loading

Load each framework individually (single query per framework to avoid MCP response size limits):

SELECT content FROM di_frameworks WHERE framework_id = 'F02' AND status = 'active';
SELECT content FROM di_frameworks WHERE framework_id = 'F04' AND status = 'active';
SELECT content FROM di_frameworks WHERE framework_id = 'supabase-reading-guide' AND status = 'active';

Read the full file on GitHub · 350 lines

Changes

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.

  1. 8d ago First seen · 350 lines · 84 tokens per session scan A a83be9f3c445

Subscribe to this mod's changes

conversation-scanner is a skill published in the GitHub repository violetfleming47/deal-intelligence (5 stars, last pushed 4mo ago), licensed MIT. It adds 84 tokens to every session and 3,939 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.