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 thuong-nc/perlytics-skill --skill dashboard-critiquegit clone --depth 1 https://github.com/thuong-nc/perlytics-skillWrote 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/thuong-nc/perlytics-skill/dashboard-critique)<a href="https://agentmods.dev/skills/thuong-nc/perlytics-skill/dashboard-critique"><img src="https://agentmods.dev/badge/skills/thuong-nc/perlytics-skill/dashboard-critique/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/thuong-nc/perlytics-skill/dashboard-critique"><img src="https://agentmods.dev/badge/skills/thuong-nc/perlytics-skill/dashboard-critique.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 | $0.00034 | $0.00477 |
| Opus 5 | $0.00017 | $0.00238 |
| Sonnet 5 | $0.00007 | $0.00095 |
| Haiku 4.5 | $0.00003 | $0.00048 |
Grade A, and why
dashboard-critique 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dashboard Critique
Purpose
Assess whether a dashboard helps people make better decisions or merely displays numbers.
When to use
Use this skill when:
- reviewing a KPI dashboard
- improving an existing report
- deciding whether a dashboard is fit for stakeholder use
When not to use
Do not use this skill when:
- the task is to diagnose a metric change in detail
- there is no reporting artifact to review
Required thinking discipline
- Judge the dashboard against decisions, not aesthetics alone.
- Check metric definitions, baselines, and comparability.
- Look for ways the dashboard could mislead a stakeholder.
- Evidence constraint: Every conclusion must cite specific data — a number, a rate, a segment, or a timeframe. Do not speculate without evidential basis. If data is insufficient, state what is missing rather than asserting an unsupported inference.
Workflow
- Identify the audience and decision use case.
- Review metric labels and definitions.
- Review baselines, comparisons, and time context.
- Review segmentation and drill-down usefulness.
- Identify likely misreads or missing context.
- Recommend the smallest changes that materially improve decision value.
Output format
- Intended audience
- What works
- What is unclear or risky
- Missing context
- Recommended changes
- Priority order
Good example
The dashboard shows weekly active users but not the baseline, target, or segmentation. A manager can see the count moved, but not whether the movement is meaningful or where it came from.
Bad example
The dashboard looks busy and should be cleaner.
Why this is bad:
- it is mostly aesthetic
- it ignores business usefulness
- it does not mention metric clarity
Practical notes
- A good dashboard usually answers a recurring decision question.
- If a metric can be interpreted multiple ways, the dashboard should not force the audience to guess.
Optional variants
- Executive dashboards: focus on signal hierarchy and decision framing.
- Analyst dashboards: focus on drill paths, definitions, and segment cuts.
What ships with it
2 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.
- 10d ago First seen · 77 lines · 34 tokens per session scan A c0b33778e50b
dashboard-critique is a skill published in the GitHub repository thuong-nc/perlytics-skill (5 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 34 tokens to every session and 477 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 2026-08-31.
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