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 agentlas-ai/agentlas-desktop --skill get-contextgit clone --depth 1 https://github.com/agentlas-ai/agentlas-desktopWrote 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/agentlas-ai/agentlas-desktop/get-context)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/get-context"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/get-context/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/agentlas-ai/agentlas-desktop/get-context"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/get-context.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 | $0.00029 | $0.00326 |
| Opus 5.5 | $0.00012 | $0.00130 |
| Sonnet 5.5 | $0.00006 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
get-context 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.
What it actually says
Skill Purpose
Establishes the fundamental requirements for a new design, prototype, or UI exploration task quickly by confirming the target surface and user outcome without long surveys.
Preconditions
- A design or build request is initiated where the specific design target (component, screen, app, website) or intended user goal is missing or ambiguous.
- Consult
$user-contextfor saved product background or user preferences when available.
Steps
- Analyze Requirements: Check if (1) design target, (2) intended user outcome, and (3) target platform (mobile/desktop/web) are clearly identified in the request.
- Targeted Clarification: If any critical piece is missing, ask exactly one focused question. Do not re-ask details that are already obvious or answered.
- Playback Brief: Once the brief is clear, play back the core target and sensible defaults in a single concise note.
- Handoff Immediately: Transition directly to the next focused workflow (
$ideate,$url-to-code, or$image-to-code) in the same turn without pausing for explicit confirmation.
Outputs
- Confirmed design brief summary (target surface, user goal, form factor).
- Execution trigger for the subsequent workflow.
Verification
- Ensure the design target and user outcome are concretely specified.
- Verify that the workflow proceeded directly to execution without blocking on redundant questions.
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 · 26 lines · 29 tokens per session scan A b956954fbf24
get-context is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 29 tokens to every session and 326 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 2026-08-31.
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