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 perniemann/pnCore --skill pn-comps-analysisgit clone --depth 1 https://github.com/perniemann/pnCoreWrote 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/perniemann/pncore/pn-comps-analysis)<a href="https://agentmods.dev/skills/perniemann/pncore/pn-comps-analysis"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-comps-analysis/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/perniemann/pncore/pn-comps-analysis"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-comps-analysis.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 | $0.00072 | $0.01089 |
| Opus 5.5 | $0.00029 | $0.00436 |
| Sonnet 5.5 | $0.00014 | $0.00218 |
| Haiku 4.5 | $0.00007 | $0.00109 |
Grade A, and why
pn-comps-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 1mo 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comparable company analysis
When to use
- Building valuation context for a pitch deck, CIM, IC memo, or initiation.
- Calibrating an entry / exit assumption against the current trading market.
- Quick-turn peer benchmarking during earnings or deal process.
Pre-requisites
Load get_skill("pn-fsi-analyst-discipline") before producing any output. State scope, as-of date, and source at the top of the deliverable.
Instructions
1. Define the peer universe
- Start from the subject company's primary SIC / GICS code and revenue band.
- Select 6–12 peers with at least three of: same subsector, comparable revenue scale, same geographic exposure, similar margin profile.
- Exclude peers with recent M&A distortion, restatements, or trading halts unless they are material comps (note and flag them).
- Document the exclusion rationale; the selection methodology is part of the deliverable.
2. Collect multiples
Preferred sources (in order): user-supplied data file → MCP financial data connector (if configured in workspace .mcp.json) → public filings footnote → analyst estimate (flag as estimate).
Key multiples to structure:
| Multiple | Numerator | Denominator | Notes |
|---|---|---|---|
| EV / LTM Revenue | Enterprise value | Last-twelve-months revenue | Useful for high-growth, negative EBITDA |
| EV / NTM Revenue | Enterprise value | Next-twelve-months consensus revenue | Forward-looking; flag as estimate |
| EV / LTM EBITDA | Enterprise value | LTM adjusted EBITDA | Core valuation anchor |
| EV / NTM EBITDA | Enterprise value | NTM consensus EBITDA | Forward; flag as estimate |
| P / NTM EPS | Market cap | NTM consensus EPS | Equity-value multiple; use for profitable peers |
State the enterprise value calculation: EV = Market cap + Net debt + Minority interest + Preferred. If balance sheet data is unavailable, note the gap and use market cap as a proxy with a caveat.
3. Compute spread statistics
For each multiple, compute: low, 25th pct, median, 75th pct, high, mean. Flag outliers (>2σ from mean) — include them in the range but exclude from the trimmed median when noted.
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.
- 1mo ago First seen · 99 lines · 72 tokens per session scan A cb4c779e72d6
pn-comps-analysis is a skill published in the GitHub repository perniemann/pnCore (0 stars, last pushed yesterday), licensed MIT. It adds 72 tokens to every session and 1,089 once invoked, about $0.0003 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 2026-09-03.
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