objection-mining

name	objection-mining
description	Aggregates objections from call notes across territory and builds a living response library. Trigger with "what are they pushing back on", "objection library", "log this objection", "what objections am I seeing", "objection patterns", or "update my objection library".
version	1.0.0

Objection Mining

Purpose: Turn individual objections from every call into a territory-wide pattern library. Every call is a data point. This skill connects them.

Input: ## Objections Logged sections in all accounts/*/discovery/ files. Output: memory/objection-library.md — append only, never overwrite.

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STEP 0 — Confirm Scope

1. Single account: "Log the objection from my last call with [company]" → Read most recent discovery/ file for that account only
2. Territory sweep: "Update my objection library" or "What are they pushing back on?" → Scan all accounts/*/discovery/ files

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STEP 1 — Scan Call Notes Files

Read all files matching accounts/*/discovery/*.md.

For each file, look for the ## Objections Logged section:

## Objections Logged
| Type | Verbatim Quote | Stage | Response Used | Outcome |

If no section found → skip it. If found → extract all rows.

Types: Timing / Budget / Authority / Trust / Fit / Competition

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STEP 2 — Parse and Classify

For each objection row:

1. Confirm or correct the Type classification
2. Note the Stage (what deal stage was this raised at?)
3. Note the Response Used and Outcome
4. Check if new or a variant of an existing one

Type	Description	Example
Timing	"Not now"	"We're heads-down until Q3"
Budget	Cost or prioritization block	"No budget allocated this year"
Authority	Needs escalation	"I'd need to check with my manager"
Trust	Skepticism	"We've heard this before and it didn't deliver"
Fit	Genuine mismatch concern	"We're too small / too big for this"
Competition	Evaluating an alternative	"We're already evaluating [competitor]"

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STEP 3 — Aggregate into Library

Read memory/objection-library.md (create if doesn't exist).

For each objection:

• Find the matching entry or create a new one
• Increment count
• Add the new verbatim quote
• Update win/loss pattern if outcome is known

Library format:

# Objection Library
*Last updated: YYYY-MM-DD | {N} objections tracked | {N} accounts*

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## Timing Objections
**Count:** {N} | **Win rate:** {N}% | **Most common stage:** {stage}

### Most Common Responses (by win rate)
1. [Response that worked — with example]
2. [Second best response]

### Verbatim Quotes (latest 5)
- "[Quote]" — {Company}, {Stage}, {Date}

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## Budget Objections
[Same structure]

## Authority Objections
[Same structure]

## Trust Objections
[Same structure]

## Fit Objections
[Same structure]

## Competition Objections
[Same structure]

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## Top 5 Objections by Frequency

| Rank | Objection | Type | Count | Win Rate | Best Response |
|------|-----------|------|-------|----------|--------------|
| 1 | | | | | |

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STEP 4 — Generate Response Templates

For any objection type where Count ≥ 3 AND no "Best Response" is documented:

Generate a template using the AAA framework:

Type: [Timing/Budget/Authority/Trust/Fit/Competition]
Pattern: "[Common version of this objection]"

AAA Response:
- Acknowledge: "[Validate without agreeing]"
- Ask: "[Reframe question to understand root cause]"
- Advance: "[Earn the next 30 seconds]"

Outcome goal: [What constitutes a win for this objection]

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STEP 5 — Save

Append to memory/objection-library.md — never overwrite the full file.

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Quality Gates

• All discovery/ files scanned for ## Objections Logged sections
• Each objection type-classified correctly
• Frequency counts updated
• Win rate updated where outcome is known
• Response templates generated for types with 3+ examples and no template
• memory/objection-library.md updated (append only)
• Top 5 frequency table updated