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 icp-refinegit 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/icp-refine)<a href="https://agentmods.dev/skills/octavehq/lfgtm/icp-refine"><img src="https://agentmods.dev/badge/skills/octavehq/lfgtm/icp-refine/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/icp-refine"><img src="https://agentmods.dev/badge/skills/octavehq/lfgtm/icp-refine.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00054 | $0.01731 |
| Opus 5 | $0.00027 | $0.00865 |
| Sonnet 5 | $0.00011 | $0.00346 |
| Haiku 4.5 | $0.00005 | $0.00173 |
Grade A, and why
icp-refine 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 — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/octave:icp-refine - ICP Intelligence
Analyze deal outcomes, conversation patterns, and qualification scores to refine your ICP definitions. Compares what your library says your ideal customer looks like against what actually wins — then recommends updates.
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:icp-refine [--period <days>] [--segment <name>] [--focus wins|losses|both]
Examples
/octave:icp-refine # Full ICP analysis (last 180 days)
/octave:icp-refine --period 90 # Last quarter
/octave:icp-refine --segment "Enterprise" # Specific segment
/octave:icp-refine --focus wins # Only analyze what's working
/octave:icp-refine --focus losses # Only analyze what's not working
Instructions
When the user runs /octave:icp-refine:
Step 1: Set Parameters
If no options specified, use defaults and confirm:
I'll analyze your deal data to refine your ICP.
Period: Last 180 days (change with --period)
Segments: All (change with --segment)
Focus: Wins and losses
Starting analysis...
Step 2: Gather Current ICP Definition
# Get current segments (this IS the ICP definition)
list_entities({ entityType: "segment" })
# Get full segment details
get_entity({ oId: "<segment_oId>" }) // for each segment
# Get current personas
list_entities({ entityType: "persona" })
get_entity({ oId: "<persona_oId>" }) // for key personas
# Get products/services (what we're selling)
list_entities({ entityType: "product" })
list_entities({ entityType: "service" })
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.
- 11d ago First seen · 252 lines · 54 tokens per session scan A 40d07c090cb1
icp-refine is a skill published in the GitHub repository octavehq/lfgtm (11 stars, last pushed 21d ago), licensed MIT. It adds 54 tokens to every session and 1,731 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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