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 Foxfire1st/agents-remember --skill dashboard-experience-reviewgit clone --depth 1 https://github.com/Foxfire1st/agents-rememberWrote 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/foxfire1st/agents-remember/dashboard-experience-review)<a href="https://agentmods.dev/skills/foxfire1st/agents-remember/dashboard-experience-review"><img src="https://agentmods.dev/badge/skills/foxfire1st/agents-remember/dashboard-experience-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/foxfire1st/agents-remember/dashboard-experience-review"><img src="https://agentmods.dev/badge/skills/foxfire1st/agents-remember/dashboard-experience-review.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 | $0.00102 | $0.02081 |
| Opus 5 | $0.00051 | $0.01040 |
| Sonnet 5 | $0.00020 | $0.00416 |
| Haiku 4.5 | $0.00010 | $0.00208 |
Grade A, and why
dashboard-experience-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 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dashboard-experience-review Dashboard Experience Review
Use this skill to review a live agents-remember cockpit dashboard (including the Task-6 control plane) against the user workflows it is supposed to support. It does not just grade rendered pixels — it asks "what would a user try to do here, and can they?": it discovers the intended workflow scenarios, detects missing views that break those workflows, finds where a user gets stuck, and judges glance-clarity, hierarchy, progressive disclosure, and observability quality.
It is a conductor. The craft dimensions (visual hierarchy, accessibility, data-viz honesty,
motion feel) are already covered by installed skills — this skill delegates to them and owns only
the layer none of them cover (scenario discovery, missing-view detection, observability-parity,
motion-as-communication, the Task-6 terminal UX). See delegation-map.md.
Findings only. This skill never edits the dashboard. A fix is a separate, gated build job. Every output is a finding, routed in the design-review triage format so it can feed that pipeline.
When to use
- Reviewing the cockpit dashboard before a release, a PR, or a demo.
- As the final review step of an ongoing dashboard build task, before its closeout.
- Investigating a "the dashboard looks fine but users can't do X" report.
- Auditing whether the dashboard honours observability-parity ("if chat or an MCP status tool can see it, the dashboard must show it").
Do not use it to fix anything, to review non-dashboard UIs, or as a substitute for the craft skills it delegates to.
Invocation modes
Stage 0 detects which mode it is running in and resolves the target accordingly.
- Standalone review. The caller points the skill at a running dashboard (frontend URL/port +
backend, default
:8765). No worktree coupling; the skill drives the running app and emits a self-contained review report. - Final step inside an ongoing task. Invoked within an active build worktree before that task's
closeout. The skill reviews the work-in-progress dashboard served from that worktree's
same-branch backend (a mismatched-branch backend renders empty — see
review-doctrine.md), so its findings inform the host task's closeout. It reads the host worktree's code/observer/projection directly rather thanmain.
What ships with it
5 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 · 135 lines · 102 tokens per session scan A 3e29bf958ccf
dashboard-experience-review is a skill published in the GitHub repository Foxfire1st/agents-remember (27 stars, last pushed today), licensed MIT. It adds 102 tokens to every session and 2,081 once invoked, about $0.0005 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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