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 octavehq/lfgtm --skill win-loss-reportgit clone --depth 1 https://github.com/octavehq/lfgtmWrote 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/octavehq/lfgtm/win-loss-report)<a href="https://agentmods.dev/skills/octavehq/lfgtm/win-loss-report"><img src="https://agentmods.dev/badge/skills/octavehq/lfgtm/win-loss-report/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/octavehq/lfgtm/win-loss-report"><img src="https://agentmods.dev/badge/skills/octavehq/lfgtm/win-loss-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 21 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00072 | $0.03729 |
| Opus 5 | $0.00036 | $0.01865 |
| Sonnet 5 | $0.00014 | $0.00746 |
| Haiku 4.5 | $0.00007 | $0.00373 |
Grade A, and why
win-loss-report 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 — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/octave:win-loss-report - Visual Win/Loss Report Builder
Generate beautiful, self-contained HTML win/loss analysis reports powered by your Octave deal intelligence. Unlike /octave:win-loss-report which outputs text-based analysis, this skill renders structured visual reports with CSS-based charts, progress indicators, comparison bars, and metric cards -- designed for leadership reviews, team retrospectives, and strategic planning.
Uses the same CSS variable / style preset system as /octave:deck.
On-brand styling — brand kit first, then generate
Resolve the brand before generating (do not skip this step). The report brand should be the workspace company's brand — that is, the Octave customer whose workspace you are operating in.
Step 1: Identify the workspace company. Call get_workspace_company to get the company name, domain/URL, and positioning. This is the company whose brand the report should use (whatever get_workspace_company returns is the brand, not the target account).
Step 2: Resolve the workspace company's brand kit. Slugify the workspace company name and check for a cached brand kit at ~/.octave/brands/<slug>/manifest.json. If a complete kit exists (has manifest.json and tokens.css), use it automatically:
- inline the kit's
tokens.css(:root+ the embedded@font-face) andget-brand-components/assets/kit_base.cssinto the output<style>; - follow
brand-kit.md→ Signature moves, and reuse the kit's real logo for topbar and footer,images/, andicons.json. If no complete kit exists → build one. Run theget-brand-componentsskill (read../../skills/get-brand-components/SKILL.mdand follow it) for the workspace company's domain. If the first attempt returns incomplete results (no logo, no colors, partial data) → retry up to 3 times with different approaches (root domain,www.prefix,/aboutsubpage). Only fall back to a generic preset after 3 genuine failures.
Step 3: Only use a generic preset as a last resort — after the workspace company's brand kit cannot be built.
What ships with it
4 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.
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 · 358 lines · 72 tokens per session scan A cef9595c9dfa
win-loss-report is a skill published in the GitHub repository octavehq/lfgtm (11 stars, last pushed 21d ago), licensed MIT. It adds 72 tokens to every session and 3,729 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…