win-loss-analysis

win-loss-analysis is a skill for Claude Code, Codex from freckle-io/deal-closed-analysis-skill. It costs 95 tokens per session (7,146 once invoked), scanned A, original, no licence file.

A report that compares CRM deals marked closed-won with those marked closed-lost. CRM means customer relationship management software, such as HubSpot or Salesforce.

In plain words
What is it for?
It is for analysing deal data from HubSpot, Salesforce, or CSV files and producing findings, dashboards, and deal stories.
Why use it?
It helps reveal which customer and deal patterns are associated with winning or losing, including gaps in the available data.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit It is for analysing deal data from HubSpot, Salesforce, or CSV files and producing findings, dashboards, and deal stories.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/freckle-io/deal-closed-analysis-skill/deal-closed-analysis-skill
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 freckle-io/deal-closed-analysis-skill --skill deal-closed-analysis-skill
Clone the repo
git clone --depth 1 https://github.com/freckle-io/deal-closed-analysis-skill

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 win-loss-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/freckle-io/deal-closed-analysis-skill/deal-closed-analysis-skill/github.svg)](https://agentmods.dev/skills/freckle-io/deal-closed-analysis-skill/deal-closed-analysis-skill)
Your own site
<a href="https://agentmods.dev/skills/freckle-io/deal-closed-analysis-skill/deal-closed-analysis-skill"><img src="https://agentmods.dev/badge/skills/freckle-io/deal-closed-analysis-skill/deal-closed-analysis-skill/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.

agentmods 80×15 button for win-loss-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/freckle-io/deal-closed-analysis-skill/deal-closed-analysis-skill"><img src="https://agentmods.dev/badge/skills/freckle-io/deal-closed-analysis-skill/deal-closed-analysis-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,146 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 unknown 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 $0.00095 $0.07146
Opus 5.5 $0.00038 $0.02858
Sonnet 5.5 $0.00019 $0.01429
Haiku 4.5 $0.00010 $0.00715

Measured 2mo ago against content hash 98ff8e142e3b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

win-loss-analysis 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 2mo 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.

SKILL.md · 556 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

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.

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. 2mo ago First seen · 556 lines · 95 tokens per session scan A 98ff8e142e3b

Subscribe to this mod's changes

win-loss-analysis is a skill published in the GitHub repository freckle-io/deal-closed-analysis-skill (5 stars, last pushed 6mo ago), with no licence file. It adds 95 tokens to every session and 7,146 once invoked, about $0.0004 per session on Opus 5.5. 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.

Related

win-loss-analysis compared with skills from other repositories

win-loss-analysis next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
win-loss-analysisfreckle-io/deal-closed-analysis-skillSkill56mo agononeA95Claude Code, Codex
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playwright-climicrosoft/playwrightSkill99ktodayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79ktodayMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill314k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code
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