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/plan-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/plan-review)<a href="https://agentmods.dev/skills/banshee-data/velocity.report/plan-review"><img src="https://agentmods.dev/badge/skills/banshee-data/velocity.report/plan-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/plan-review"><img src="https://agentmods.dev/badge/skills/banshee-data/velocity.report/plan-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 | $0.00031 | $0.00830 |
| Opus 5.5 | $0.00012 | $0.00332 |
| Sonnet 5.5 | $0.00006 | $0.00166 |
| Haiku 4.5 | $0.00003 | $0.00083 |
Grade A, and why
plan-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 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: plan-review
Review a design plan, feature spec, or backlog item. Produces a structured review covering scope, architectural soundness, risks, and recommended sequencing.
Usage
/plan-review path/to/plan.md
/plan-review "lidar L7 scene layer"
/plan-review # review the most recently changed plan doc
Procedure
1. Locate the plan
If a path is given, read it directly. If a name is given, search docs/plans/ for a matching file. If no argument, identify the most recently modified file in docs/plans/.
Also read:
docs/BACKLOG.md(for milestone context)docs/DECISIONS.md(for related decisions)- Any files the plan references in its first section
2. Scope review (ruth's lens)
Answer each question:
- What is the actual decision this plan is trying to make?
- What is explicitly in scope? What is explicitly out of scope?
- Is there a NOT-in-scope list? If not, draft one.
- Does the plan try to resolve too much at once? Flag overreach.
- What happens if we do nothing?
- What existing code already solves part of this problem?
3. Technical soundness review (grace's lens)
- Are component boundaries clean?
- Is data flow described for happy path and failure paths?
- Is the migration path defined for existing deployments?
- Are there any privacy concerns? (camera/licence plate/PII/cloud transmission)
- Does the plan fit within Raspberry Pi 4 constraints?
- Are new dependencies justified?
4. Risk register (flo's lens)
Produce a risk register:
| Risk | Likelihood | Impact | Mitigation |
| ------------------ | ------------ | ------------ | ---------- |
| [risk description] | Low/Med/High | Low/Med/High | [action] |
Minimum risk categories to check: technical, integration, data/migration, privacy, scope creep, dependency.
5. Sequencing check (flo's lens)
- Are tasks ordered to unblock dependencies early?
- Are the highest-risk items tackled first?
- Is there an incremental delivery path (not big-bang)?
- Does every task have acceptance criteria?
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 · 125 lines · 31 tokens per session scan A 471b203aefba
plan-review is a skill published in the GitHub repository banshee-data/velocity.report (11 stars, last pushed today), licensed Apache-2.0. It adds 31 tokens to every session and 830 once invoked, about $0.0001 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 2026-09-25.
plan-review compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| plan-reviewbanshee-data/velocity.report | Skill | 11 | today | Apache-2.0 | A | 31 | 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 |