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 pekral/cursor-rules --skill laravel-telescopegit clone --depth 1 https://github.com/pekral/cursor-rulesWrote 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/pekral/cursor-rules/laravel-telescope)<a href="https://agentmods.dev/skills/pekral/cursor-rules/laravel-telescope"><img src="https://agentmods.dev/badge/skills/pekral/cursor-rules/laravel-telescope/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/pekral/cursor-rules/laravel-telescope"><img src="https://agentmods.dev/badge/skills/pekral/cursor-rules/laravel-telescope.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 | $0.01191 |
| Opus 5 | $0.00017 | $0.00596 |
| Sonnet 5 | $0.00007 | $0.00238 |
| Haiku 4.5 | $0.00003 | $0.00119 |
Grade A, and why
laravel-telescope 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Constraints
- If the current project uses Laravel, also apply
@rules/laravel/laravel.mdc,@rules/laravel/architecture.mdc,@rules/laravel/filament.mdc, and@rules/laravel/livewire.mdc
Purpose
Use this skill when you need to investigate a specific Laravel Telescope request, read its runtime data, find the same request directly in the Telescope database tables, and propose actionable optimizations.
The goal is practical diagnosis from real telemetry, not generic performance advice.
When to use
Use this skill when the task asks for any of the following:
- analyze output from a Telescope URL
- inspect one concrete Telescope request in detail
- map a Telescope UI request to DB records
- verify request behavior from
telescope_entriesand related tables - propose optimization opportunities based on observed request/query/job/cache/log data
When not to use
Do not use this skill when:
- the project does not use Laravel Telescope
- no Telescope URL, request id, or filter context is available
- the user only wants generic Laravel performance tips without Telescope evidence
If Telescope UI or DB access is missing, continue with static analysis and clearly state limitations.
Expected inputs
The skill can work with:
- Telescope URL (preferred)
- request UUID / entry UUID
- environment access (local, staging, production read-only)
- DB credentials for Telescope storage
- logs or screenshots exported from Telescope
The skill should proceed with whatever is available and not block on perfect input.
Required workflow
Follow these steps in order.
1. Parse the Telescope target from URL
- Extract environment, host, path, query params, and request identifier from the provided URL.
- Identify whether the URL points to requests, exceptions, queries, jobs, cache, dumps, or logs.
- Capture all filters (time window, status code, tag, batch, family hash, etc.) because they affect record matching.
2. Read the same request in Telescope UI data
What ships with it
3 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 · 175 lines · 34 tokens per session scan A 3ec38de76eab
laravel-telescope is a skill published in the GitHub repository pekral/cursor-rules (7 stars, last pushed 9d ago), licensed MIT. It adds 34 tokens to every session and 1,191 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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