matteotitta
Registry indexed
win-loss
Analyses sales call transcripts (and churn or renewal calls) to find why deals are won, lost, kept or churned. Reads each call across six dimensions (product, messaging, sales process, pricing, competition, customer context), pulls verbatim quotes with the speaker named, counts h
Overview
Analyses sales call transcripts (and churn or renewal calls) to find why deals are won, lost, kept or churned. Reads each call across six dimensions (product, messaging, sales process, pricing, competition, customer context), pulls verbatim quotes with the speaker named, counts how often each pattern appears, and writes findings with recommendations. Works with any recorder export or pasted text. Triggers: "win/loss analysis", "why do we lose", "why do we win", "analyse these sales calls", "lost deals", "churn analysis", "objection patterns". Feeds /positioning and /messaging. Not for general meeting summaries or competitor research (use /competitor-research).
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Win-loss
Turn sales calls into evidence about why people buy and why they don't. The quotes are the main product; the summary is secondary. Every pattern you report has to trace back to something a person said on a call.
When to use it
- After 5 or more closed deals with recordings or notes.
- Before positioning or messaging work, to replace opinions about objections with evidence.
- When win rate drops, or a competitor starts showing up in losses.
- Monthly, as a standing review for a team with steady deal flow.
Don't use it for one-off meeting notes, for researching competitors from the outside (/competitor-research), or for picking an ICP on its own (feed the findings into /icp-research).
Inputs
Required: transcripts, each with the customer (or a code name) and the outcome: win, loss, retention or churn. If the outcome isn't given, ask. Only infer it when the call itself states it.
Optional: deal size and stage, competitor names to watch for, context/icp/ and context/competitors/ for cross-referencing.
Paths. Write to context/win-loss/MMYY-win-loss.md. Keep a short context/win-loss/win-loss-strategy.md across runs: decisions made, definitions agreed, things to stop doing. Read it first on every run. Agency or consultant? Swap context/ for clients/<client>/context/ throughout.
Tools. None needed beyond the transcripts. If a call recorder or CRM is connected, pull from it; otherwise the user pastes or uploads files.
Before you analyse
- Normalise the format. Recorder exports, subtitle files, JSON and pasted text all become one shape: speaker-attributed turns, with timestamps where they exist.
- Redact personal data. Mask end-customer names, emails, phone and account numbers. Keep roles, company type and deal context.
- Bind every claim to a quote. A finding without a quote and a named speaker role doesn't ship.
The six dimensions
| Dimension | Win signals | Loss signals |
|---|---|---|
| Product | "Exactly what we need" | "It doesn't do X" |
| Messaging | "Now I see why this matters" | "What does it actually do?" |
| Sales process | "You understood our problem" | "The demo missed our use case" |
| Pricing | "Fair for what we get" | "Over budget", "too expensive" |
| Competition | "Chose you over Y" | "Going with Y" |
| Customer context | "We need this by Q2" | "No rush, maybe next year" |
Steps
- Read the strategy file if one exists, and apply its locked definitions.
- Process each call. Classify the outcome, tag speakers (buyer, champion, rep), and pull quotes against the six dimensions. Produces: a per-call evidence table.
- Aggregate by outcome. Group wins, losses, retention and churn. Count how many calls support each pattern ("4 of 7 losses").
- Rank patterns. Three or more mentions is a pattern. Two is emerging. One is a single mention, labelled as unconfirmed.
- Cross-reference by segment, deal size or competitor where the data allows. Look across at least three cuts, not just competitor.
- Separate product gaps from sales execution. They go to different teams.
- Write insights. For each: the pattern, the evidence with frequency and quotes, the confidence, and what to do about it.
- Update the strategy file with new decisions and definitions.
- Hand off to
/positioningand/messaging.
Output shape
Open with a 3-line TLDR and the sample size, stated once. Then: an executive summary, top win drivers, top loss drivers, objection themes with suggested responses, competitor mentions, a per-dimension breakdown, recommendations split into product, messaging and sales, and an appendix of quotes by call.
Confidence: high is 3 or more consistent calls, medium is 2 or strong indirect signals, low is a single mention.
What good looks like
- Every finding has a frequency and at least one verbatim quote with a speaker role.
- Patterns are described as "associated with", not "caused by".
- Small samples are flagged clearly. Under 5 wins and 5 losses, findings are directional.
- Dimensions with no data say "not discussed in transcripts".
- A seller could use the objection section on their next call.
Mistakes to avoid
- Summarising what buyers said instead of quoting them.
- Treating one memorable call as a pattern.
- Mixing up what the rep said with what the buyer said.
- Reading cause into correlation ("long cycles lose deals").
- Keeping customer names or emails in the saved file.
Chain
Step 4 of the suggested chain: /company-context → /icp-research → /competitor-research → win-loss → /expert-pov → /tov-guidelines → /brand-kit → /positioning → /messaging → /funnel-strategy → /goals.
File metadata
name: win-loss description: >- Analyses sales call transcripts (and churn or renewal calls) to find why deals are won, lost, kept or churned. Reads each call across six dimensions (product, messaging, sales process, pricing, competition, customer context), pulls verbatim quotes with the speaker named, counts how often each pattern appears, and writes findings with recommendations. Works with any recorder export or pasted text. Triggers: "win/loss analysis", "why do we lose", "why do we win", "analyse these sales calls", "lost deals", "churn analysis", "objection patterns". Feeds /positioning and /messaging. Not for general meeting summaries or competitor research (use /competitor-research). version: '1.0.0' license: MIT
View original text
---
name: win-loss
description: >-
Analyses sales call transcripts (and churn or renewal calls) to find why deals are won, lost, kept or
churned. Reads each call across six dimensions (product, messaging, sales process, pricing,
competition, customer context), pulls verbatim quotes with the speaker named, counts how often each
pattern appears, and writes findings with recommendations. Works with any recorder export or pasted
text. Triggers: "win/loss analysis", "why do we lose", "why do we win", "analyse these sales calls",
"lost deals", "churn analysis", "objection patterns". Feeds /positioning and /messaging. Not for
general meeting summaries or competitor research (use /competitor-research).
version: '1.0.0'
license: MIT
---
# Win-loss
Turn sales calls into evidence about why people buy and why they don't. The quotes are the main product; the summary is secondary. Every pattern you report has to trace back to something a person said on a call.
## When to use it
- After 5 or more closed deals with recordings or notes.
- Before positioning or messaging work, to replace opinions about objections with evidence.
- When win rate drops, or a competitor starts showing up in losses.
- Monthly, as a standing review for a team with steady deal flow.
Don't use it for one-off meeting notes, for researching competitors from the outside (`/competitor-research`), or for picking an ICP on its own (feed the findings into `/icp-research`).
## Inputs
**Required:** transcripts, each with the customer (or a code name) and the outcome: win, loss, retention or churn. If the outcome isn't given, ask. Only infer it when the call itself states it.
**Optional:** deal size and stage, competitor names to watch for, `context/icp/` and `context/competitors/` for cross-referencing.
**Paths.** Write to `context/win-loss/MMYY-win-loss.md`. Keep a short `context/win-loss/win-loss-strategy.md` across runs: decisions made, definitions agreed, things to stop doing. Read it first on every run. Agency or consultant? Swap `context/` for `clients/<client>/context/` throughout.
**Tools.** None needed beyond the transcripts. If a call recorder or CRM is connected, pull from it; otherwise the user pastes or uploads files.
## Before you analyse
- **Normalise the format.** Recorder exports, subtitle files, JSON and pasted text all become one shape: speaker-attributed turns, with timestamps where they exist.
- **Redact personal data.** Mask end-customer names, emails, phone and account numbers. Keep roles, company type and deal context.
- **Bind every claim to a quote.** A finding without a quote and a named speaker role doesn't ship.
## The six dimensions
| Dimension | Win signals | Loss signals |
|---|---|---|
| Product | "Exactly what we need" | "It doesn't do X" |
| Messaging | "Now I see why this matters" | "What does it actually do?" |
| Sales process | "You understood our problem" | "The demo missed our use case" |
| Pricing | "Fair for what we get" | "Over budget", "too expensive" |
| Competition | "Chose you over Y" | "Going with Y" |
| Customer context | "We need this by Q2" | "No rush, maybe next year" |
## Steps
1. **Read the strategy file** if one exists, and apply its locked definitions.
2. **Process each call.** Classify the outcome, tag speakers (buyer, champion, rep), and pull quotes against the six dimensions. *Produces:* a per-call evidence table.
3. **Aggregate by outcome.** Group wins, losses, retention and churn. Count how many calls support each pattern ("4 of 7 losses").
4. **Rank patterns.** Three or more mentions is a pattern. Two is emerging. One is a single mention, labelled as unconfirmed.
5. **Cross-reference** by segment, deal size or competitor where the data allows. Look across at least three cuts, not just competitor.
6. **Separate product gaps from sales execution.** They go to different teams.
7. **Write insights.** For each: the pattern, the evidence with frequency and quotes, the confidence, and what to do about it.
8. **Update the strategy file** with new decisions and definitions.
9. **Hand off** to `/positioning` and `/messaging`.
## Output shape
Open with a 3-line TLDR and the sample size, stated once. Then: an executive summary, top win drivers, top loss drivers, objection themes with suggested responses, competitor mentions, a per-dimension breakdown, recommendations split into product, messaging and sales, and an appendix of quotes by call.
Confidence: high is 3 or more consistent calls, medium is 2 or strong indirect signals, low is a single mention.
## What good looks like
- Every finding has a frequency and at least one verbatim quote with a speaker role.
- Patterns are described as "associated with", not "caused by".
- Small samples are flagged clearly. Under 5 wins and 5 losses, findings are directional.
- Dimensions with no data say "not discussed in transcripts".
- A seller could use the objection section on their next call.
## Mistakes to avoid
- Summarising what buyers said instead of quoting them.
- Treating one memorable call as a pattern.
- Mixing up what the rep said with what the buyer said.
- Reading cause into correlation ("long cycles lose deals").
- Keeping customer names or emails in the saved file.
## Chain
Step 4 of the suggested chain: `/company-context` → `/icp-research` → `/competitor-research` → **win-loss** → `/expert-pov` → `/tov-guidelines` → `/brand-kit` → `/positioning` → `/messaging` → `/funnel-strategy` → `/goals`.
Review the source
Price & running costs
- Get the skill
- Price unconfirmed
- Run it
- Requirements have not been confirmed. Check the source for agent, API and service charges.
- License
- MIT
- Price unconfirmed
- We have not confirmed a price for this skill. Existing source and install links remain available.
Free to get does not mean free to run. Price labels are not safety ratings. Submit pricing information →
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- AI review approval is missing
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- GitHub adoption: 63 GitHub stars
- Stars/forks activity: 63 stars, 19 forks; issue activity unavailable in current metadata
- Review status: AI review approval is missing
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Start with one small task
- 1Read the source. Confirm the input, expected output, dependencies and permissions.
- 2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
- 3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.
Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.
Source & usage notes
IndexedStatic Checked
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
- Source repository
- matteotitta/repo-structure-in-house
- License
- MIT
- Version
- 1.0.0
- Last GitHub push
- Oct 14, 2026
- Registry updated
- Oct 14, 2026
- Instruction path
- .claude/skills/win-loss/SKILL.md @ 4016985f52ad
Version reported in registry metadata; check source releases before relying on it.
Quality
59/100
Promising
Trust
68/100
Sandbox only
Audit
77/100
Risky
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- AI review approval is missing
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- GitHub adoption: 63 GitHub stars
- Stars/forks activity: 63 stars, 19 forks; issue activity unavailable in current metadata
- Review status: AI review approval is missing
- Verified installs
- —
- Outcomes
- —
Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.
Agent access
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
More details
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"skill": {
"slug": "matteotitta-win-loss",
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"description": "Analyses sales call transcripts (and churn or renewal calls) to find why deals are won, lost, kept or churned. Reads each call across six dimensions (product, messaging, sales process, pricing, competition, customer context), pulls verbatim quotes with the speaker named, counts how often each pattern appears, and writes findings with recommendations. Works with any recorder export or pasted text. Triggers: \"win/loss analysis\", \"why do we lose\", \"why do we win\", \"analyse these sales calls\", \"lost deals\", \"churn analysis\", \"objection patterns\". Feeds /positioning and /messaging. Not for general meeting summaries or competitor research (use /competitor-research).",
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"GitHub adoption: 63 GitHub stars",
"Stars/forks activity: 63 stars, 19 forks; issue activity unavailable in current metadata",
"Review status: AI review approval is missing"
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"supply": {
"track": "Marketing and growth automation",
"scenario": "Sales and CRM",
"maintenance": "3d since push",
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"alternative_skills": [
{
"slug": "phuryn-competitive-battlecard",
"name": "competitive-battlecard",
"url": "https://www.openagentskill.com/skills/phuryn-competitive-battlecard",
"stars": 26853,
"install_command": "npx skills add phuryn/pm-skills --skill competitive-battlecard",
"trust_score": 86,
"audit_score": 88
},
{
"slug": "coreyhaines31-copy-editing",
"name": "copy-editing",
"url": "https://www.openagentskill.com/skills/coreyhaines31-copy-editing",
"stars": 55183,
"install_command": "npx skills add coreyhaines31/marketingskills --skill copy-editing",
"trust_score": 87,
"audit_score": 89
},
{
"slug": "coreyhaines31-influencer-marketing",
"name": "influencer-marketing",
"url": "https://www.openagentskill.com/skills/coreyhaines31-influencer-marketing",
"stars": 55183,
"install_command": "npx skills add coreyhaines31/marketingskills --skill influencer-marketing",
"trust_score": 84,
"audit_score": 87
}
],
"do_not_use_when": [
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"No OpenAgentSkill engagement data yet",
"Audit risk risky exceeds max_risk=medium",
"Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required",
"AI review approval is missing",
"This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.",
"Quality score needs review"
],
"agent_contract": {
"task_input": "Use win-loss in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 76/100 Strong shortlist",
"Audit: 77/100 Risky",
"Safety: 61/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "matteotitta-win-loss (win-loss)",
"install_command": "npx skills add matteotitta/repo-structure-in-house --skill win-loss",
"risk_summary": "Risky; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "matteotitta-win-loss",
"task": "Use win-loss in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/matteotitta-win-loss",
"api": "https://www.openagentskill.com/api/agent/skills/matteotitta-win-loss",
"audit": "https://www.openagentskill.com/skills/matteotitta-win-loss/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=matteotitta-win-loss&task=Use%20win-loss%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20win-loss%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20win-loss%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/matteotitta-win-loss/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/matteotitta-win-loss"
}
}For the creator
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- matteotitta
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- OpenAgentSkill community index
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