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 FlowRegSuite/flowreg-agent-skills --skill flowreg-register-sessiongit clone --depth 1 https://github.com/FlowRegSuite/flowreg-agent-skillsWrote 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/flowregsuite/flowreg-agent-skills/flowreg-register-session)<a href="https://agentmods.dev/skills/flowregsuite/flowreg-agent-skills/flowreg-register-session"><img src="https://agentmods.dev/badge/skills/flowregsuite/flowreg-agent-skills/flowreg-register-session/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/flowregsuite/flowreg-agent-skills/flowreg-register-session"><img src="https://agentmods.dev/badge/skills/flowregsuite/flowreg-agent-skills/flowreg-register-session.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 | $0.00070 | $0.01784 |
| Opus 5 | $0.00035 | $0.00892 |
| Sonnet 5 | $0.00014 | $0.00357 |
| Haiku 4.5 | $0.00007 | $0.00178 |
Grade A, and why
flowreg-register-session 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 9d 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-recording session alignment
1. Purpose
Put several recordings into one coordinate system with one objective valid mask, so that a region of interest means the same thing in every recording and comparisons across time are fair.
2. Use this skill when
- Several separately acquired recordings must share coordinates.
- A longitudinal study needs one ROI across days or sessions.
- A study is large enough to need checkpointing, resume, or cluster execution.
- You need a consensus mask of pixels observed in-bounds in all recordings.
3. Do not use this skill when
- There is one recording, even if it is split across several files by an instrument limit → use
flowreg-register-2dand pass the file list. - The recordings will be analysed independently and need no shared ROI → run
flowreg-register-2dper recording; session machinery adds cost without benefit. - The problem is axial drift relative to a reference volume →
flowreg-correct-z-drift. - The data are volumes →
flowreg-register-3d.
4. Required inputs and metadata
- A session root directory and a glob pattern that selects exactly the intended recordings.
- Which recording is the centre (anchor). The default is the lexicographic middle file, which is not necessarily the chronological middle — check and set it explicitly if they differ.
- Consistent channel count, dimensions and axis order across recordings. Verify; do not assume.
- Recording order, and whether it is chronological.
- A writable output root and final-results directory, outside the source data.
- For cluster execution: scheduler type, and whether array jobs or Dask are intended.
5. Preflight checks
- Read
references/runtime-capability.mdfor the verified stage entry points and CLI. - Resolve the file list from root and pattern, and show it to the user. A wrong glob silently changes the science.
- Confirm every recording has the same channel count, dimensions and axis order.
- Confirm the recordings are genuinely separate acquisitions, not chunks of one.
- Confirm the centre choice, and say why it is representative.
- Check free disk against the estimated total: session mode writes a corrected copy of every recording, plus averages, masks and optionally reprojected videos.
- Check whether z offsets are suspected between recordings — see section 7.
What ships with it
3 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.
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.
- 9d ago First seen · 153 lines · 70 tokens per session scan A dcab948f0b19
flowreg-register-session is a skill published in the GitHub repository FlowRegSuite/flowreg-agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 70 tokens to every session and 1,784 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 2026-08-31.
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