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 call-analyzergit 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/call-analyzer)<a href="https://agentmods.dev/skills/octavehq/lfgtm/call-analyzer"><img src="https://agentmods.dev/badge/skills/octavehq/lfgtm/call-analyzer/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/call-analyzer"><img src="https://agentmods.dev/badge/skills/octavehq/lfgtm/call-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.02275 |
| Opus 5 | $0.00029 | $0.01137 |
| Sonnet 5 | $0.00012 | $0.00455 |
| Haiku 4.5 | $0.00006 | $0.00228 |
Grade A, and why
call-analyzer 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 10d 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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/octave:call-analyzer - Conversation Analysis
Analyze email threads, call transcripts, and sales conversations against your Octave library. Evaluates messaging resonance, Motion ICP narrative adherence, and competitive differentiation. Provides actionable insights, suggested improvements, and draft follow-ups.
Principles
Follow these standards during generation. Read each before producing output.
Content and language:
- Editorial rules — no AI-isms, banned vocabulary, honest analyst tone
- Information principles — lead with conclusions, evidence-backed claims, narrative arc
Presentation:
- Presentation principles — use for any visual output (HTML, dashboards, tables); text follows the editorial rules above
Octave data:
- Octave value — prioritize grounded workspace data over generic AI content
Usage
/octave:call-analyzer [--type email|call|chat]
Examples
/octave:call-analyzer # Interactive - paste content
/octave:call-analyzer --type email # Analyze email thread
/octave:call-analyzer --type call # Analyze call transcript
Instructions
When the user runs /octave:call-analyzer:
Step 1: Get Content to Analyze
What would you like me to analyze?
1. Paste an email thread
2. Paste a call transcript
3. Paste a chat/message thread
4. Provide a file path
(Paste content below or tell me the file path)
Accept pasted content or read from file. Content can be:
- Email thread (with headers or without)
- Call transcript (with speaker labels or without)
- Chat/messaging thread
- Meeting notes
Step 2: Parse and Structure the Content
For Email: Extract:
- Participants (internal vs external)
- Thread direction (outbound, inbound, back-and-forth)
- Key messages from each party
- Current status (awaiting response, ended, etc.)
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.
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.
- 10d ago First seen · 325 lines · 58 tokens per session scan A 75afe7d7379e
call-analyzer is a skill published in the GitHub repository octavehq/lfgtm (11 stars, last pushed 20d ago), licensed MIT. It adds 58 tokens to every session and 2,275 once invoked, about $0.0003 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.
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