Borrowing it
Nothing to install: this file belongs to banshee-data/velocity.report. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/banshee-data/velocity.report/main/.claude/skills/experiment-review/SKILL.mdgit clone --depth 1 https://github.com/banshee-data/velocity.reportWrote 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/banshee-data/velocity.report/experiment-review)<a href="https://agentmods.dev/skills/banshee-data/velocity.report/experiment-review"><img src="https://agentmods.dev/badge/skills/banshee-data/velocity.report/experiment-review/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/banshee-data/velocity.report/experiment-review"><img src="https://agentmods.dev/badge/skills/banshee-data/velocity.report/experiment-review.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 | $0.00088 | $0.02590 |
| Opus 5.5 | $0.00035 | $0.01036 |
| Sonnet 5.5 | $0.00018 | $0.00518 |
| Haiku 4.5 | $0.00009 | $0.00259 |
Grade A, and why
experiment-review 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 today.
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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: experiment-review
Read what the experiments established, decide what to run next for one goal, and leave the
queue in a state /run-experiments can pick up overnight and a person can pick up at the
annotation window in the morning. The method is the one the
October 18 review used for the
following-distance metric: the chain from a capture to the product's figure, each link's measured
state, and the cheapest experiment or the one labelled window that moves the weakest link. It is
the weekly queue review the
experiment queue plan
asks for, and it writes specs, backlog edits and a review; it approves nothing.
Usage
/experiment-review # the current goal, the next 7 days
/experiment-review following distance --days 7 # name the goal and the horizon
/experiment-review --area l5id --area geom # only these areas' lines
Run it weekly, after the Monday research briefing and before an overnight /run-experiments,
or whenever a run's reports land and the queue has gone quiet.
1. Read the state, not the memory of it
Everything below is read at origin/main's head, and the commit goes in the review's
provenance.
git fetch origin main && git log --oneline -40 origin/main
go run ./cmd/tools/experiments next # the open queue and what each waits on
go run ./cmd/tools/experiments status # approved experiments' units and time left
gh pr list --state open # or the GitHub tools; what is in flight
Then, in this order:
data/experiments/DEPENDENCIES.md: every answered experiment's report, every open one's dependencies and estimates, the longest open chain.- The Recommendations, Summary and Limitations of every report the answered specs name, newest first. A recommendation is a question with no identifier until a spec carries it; list each one and whether a spec already does.
- The goal's plan and sprint plan: the ledger of gates, what each gate's current state and remaining evidence are, and the backlog sections the goal lives in.
- The briefings under
docs/lidar/operations/brief/for their Open questions and Decisions, anddocs/DECISIONS.mdfor what was decided and what it was deferred on. - The memory notes of earlier overnight runs, where the session has them: which held-out segments were read for which measure, and the traps met.
- The labelling tooling's state:
docs/lidar/operations/point-annotation-tool.md,label-sets.md, and the plans' status lines, so a labelling task is sized against the tools that exist today, not the ones planned.
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.
- today Changed · +1 lines cb0447649159
- 19d ago First seen · 172 lines · 88 tokens per session scan A cbf2e2494d74
experiment-review is a skill published in the GitHub repository banshee-data/velocity.report (11 stars, last pushed today), licensed Apache-2.0. It adds 88 tokens to every session and 2,590 once invoked, about $0.0004 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 2026-10-18.
experiment-review compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| experiment-reviewbanshee-data/velocity.report | Skill | 11 | today | Apache-2.0 | A | 88 | Claude Code |
| analyzing-network-traffic-for-incidentsmukul975/Anthropic-Cybersecurity-Skills | Skill | 36k | 2mo ago | Apache-2.0 | A | 91 | Claude Code |
| analyzing-network-packets-with-scapymukul975/Anthropic-Cybersecurity-Skills | Skill | 36k | 2mo ago | Apache-2.0 | A | 75 | Claude Code |
| analyzing-network-traffic-with-wiresharkmukul975/Anthropic-Cybersecurity-Skills | Skill | 36k | 2mo ago | Apache-2.0 | B | 49 | Claude Code |
| whitebox-toolsznlgis/opengis-skills | Skill | 76 | 10d ago | MIT | A | 119 | Claude Code, Codex |
| performing-network-packet-capture-analysisxalgorix/xalgorix | Skill | 1.3k | yesterday | Apache-2.0 | C | 62 | Claude Code, Codex |
| pdalznlgis/opengis-skills | Skill | 76 | 10d ago | MIT | B | 90 | Claude Code, Codex |