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 agentmods add skills/quantskills/agent-quantspace/factor_miningnpx skills add quantskills/agent-quantspace --skill factor_mininggit clone --depth 1 https://github.com/quantskills/agent-quantspaceWrote 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/quantskills/agent-quantspace/factor_mining)<a href="https://agentmods.dev/skills/quantskills/agent-quantspace/factor_mining"><img src="https://agentmods.dev/badge/skills/quantskills/agent-quantspace/factor_mining.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.05345 |
| Opus 5 | $0.00023 | $0.02672 |
| Sonnet 5 | $0.00009 | $0.01069 |
| Haiku 4.5 | $0.00005 | $0.00534 |
Grade A, and why
factor_mining 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 5d 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.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
23 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.
- __init__.py 4.3 KB runs code
- adapters/__init__.py 1.3 KB runs code
- adapters/analyze.py 71 KB runs code
- adapters/compute.py 21 KB runs code
- adapters/execution_identity.py 5.7 KB runs code
- adapters/failure_codes.py 9.5 KB runs code
- adapters/formula.py 20 KB runs code
- adapters/panel.py 8.3 KB runs code
- adapters/series_codec.py 17 KB runs code
- adapters/store.py 28 KB runs code
- budget.py 6.3 KB runs code
- contracts.py 72 KB runs code
- controller.py 191 KB runs code
- event_chain.py 9.7 KB runs code
- events.py 4.5 KB runs code
- identity.py 892 B runs code
- isolation.py 21 KB runs code
- objects.py 21 KB runs code
- policies.py 3.6 KB runs code
- ports.py 3.9 KB runs code
- replay_semantics.py 114 KB runs code
- snapshots.py 12 KB runs code
- state.py 17 KB runs code
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.
- 5d ago First seen · 441 lines · 46 tokens per session scan A 2f46d878a4a4
factor_mining is a skill published in the GitHub repository quantskills/agent-quantspace (56 stars, last pushed 3d ago), licensed GPL-3.0. It adds 46 tokens to every session and 5,345 once invoked, about $0.0002 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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