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 duthaho/claudekit --skill plan-review-experiencegit clone --depth 1 https://github.com/duthaho/claudekitWrote 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/duthaho/claudekit/plan-review-experience)<a href="https://agentmods.dev/skills/duthaho/claudekit/plan-review-experience"><img src="https://agentmods.dev/badge/skills/duthaho/claudekit/plan-review-experience/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/duthaho/claudekit/plan-review-experience"><img src="https://agentmods.dev/badge/skills/duthaho/claudekit/plan-review-experience.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 | $0.00121 | $0.02534 |
| Opus 5 | $0.00060 | $0.01267 |
| Sonnet 5 | $0.00024 | $0.00507 |
| Haiku 4.5 | $0.00012 | $0.00253 |
Grade A, and why
plan-review-experience 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 10d 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Review — Experience Dimension
Overview
The experience-dimension reviewer for plan-review. Scores five sub-dimensions:
information hierarchy, state coverage, accessibility, DX ergonomics, and AI-slop
avoidance. UX and DX in one pass reflects that "user" and "developer" are both
human consumers of an interface — what differs is the surface (a screen vs an
API/CLI), not the rigor required. The skill produces scored findings paired
with concrete fixes the plan author can apply. Used by plan-review's orchestrator
in parallel with plan-review-architecture.
When to Use
- Invoked by
plan-reviewas one of its two parallel reviewers - The user wants an experience pass on a plan without the architecture review
- A plan has been edited substantially in user-facing or API-facing areas
When NOT to Use
- The plan has no user-facing or developer-facing surface (pure internal job; experience review will produce noise)
- The change is single-task and the experience implications are obvious
Process
Step 1: Pre-read
Goal: Identify the surfaces the plan touches.
Inputs: The plan file. Optionally: the spec, existing UI mockups, or API specs.
Actions:
- Read the spec and plan.
- Identify each user-facing or developer-facing surface in the plan: screens, modals, error states, API endpoints, CLI flags, config keys, log lines, error messages, docs.
- For each, note: who consumes this, in what context, with what level of familiarity.
Output: A surfaces inventory: <surface> — <consumer> — <context>.
Step 2: Score the five sub-dimensions
Goal: 5 scores with cited findings.
Inputs: The plan and the surfaces inventory.
Actions: For each sub-dimension below, score 0-10 and write at least one finding citing a plan task or section.
- Information hierarchy (0-10)
- For each user-facing surface: does the plan name what's primary, secondary, tertiary?
- Does the plan say what the user sees first?
- Score 10 = hierarchy is unambiguous from the plan.
- Score 5 = the plan describes what's on a screen but not what's emphasized.
- Score 0 = the plan lists features without ordering.
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.
- 10d ago First seen · 187 lines · 121 tokens per session scan A 99a8497e9d5a
plan-review-experience is a skill published in the GitHub repository duthaho/claudekit (97 stars, last pushed 1mo ago), licensed MIT. It adds 121 tokens to every session and 2,534 once invoked, about $0.0006 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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