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 minihellboy/factorminer --skill factor-reportgit clone --depth 1 https://github.com/minihellboy/factorminerWrote 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/minihellboy/factorminer/factor-report)<a href="https://agentmods.dev/skills/minihellboy/factorminer/factor-report"><img src="https://agentmods.dev/badge/skills/minihellboy/factorminer/factor-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/minihellboy/factorminer/factor-report"><img src="https://agentmods.dev/badge/skills/minihellboy/factorminer/factor-report.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 | $0.00080 | $0.00565 |
| Opus 5.5 | $0.00032 | $0.00226 |
| Sonnet 5.5 | $0.00016 | $0.00113 |
| Haiku 4.5 | $0.00008 | $0.00056 |
Grade A, and why
factor-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 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.
What it actually says
Factor Report
This skill turns a finished run into reviewable artifacts: a static report, plots, and portable exports.
Workflow
1. Static report
factorminer report output/run1/factor_library.json \
--session-log output/run1/session_log.json \
--format markdown --output output/run1/report.md
--format—markdownorhtml. HTML is self-contained (no JavaScript).--session-log— includes run metadata (iterations, yield rate).--benchmark path.json— fold in benchmark results; repeatable.
The report defines every admission metric inline, lists each factor with its formula and IC/ICIR/correlation, and warns on stale artifacts.
2. Plots
factorminer -o output/run1 visualize output/run1/factor_library.json \
--data market_data.csv --period test \
--correlation --ic-timeseries --quintile --format png
3. Export the library
factorminer export output/run1/factor_library.json --format formulas --output output/run1/formulas.txt
--format options: json (full library), csv (tabular metrics), formulas (plain formula list for handoff).
Assembling the research note
A complete note pairs the generated report with narrative the analyst can sign off on:
- Objective & data — universe, horizon, split boundaries, validation status.
- Method — loop used (Ralph/Helix), features enabled, iteration budget.
- Library — admitted factors with formulas and out-of-sample IC/ICIR.
- Composite — backtest result net of costs, with the decay caveat.
- Benchmark — comparison vs. baselines, if run.
- Limitations — overfit risk, capacity, what was not tested.
Guardrails
- The report presents results; it does not certify them. Frame it as research staged for human review.
- Quote out-of-sample metrics as the headline; never the in-sample number.
- Cite the run directory so every figure is reproducible via
factorminer session inspect.
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 · 58 lines · 80 tokens per session scan A 51d13aa01412
factor-report is a skill published in the GitHub repository minihellboy/factorminer (123 stars, last pushed yesterday), licensed MIT. It adds 80 tokens to every session and 565 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 2026-08-30.
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