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 reportgit 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/report)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/report"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/report/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/report"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/report.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 | $0.00012 | $0.00294 |
| Opus 5.5 | $0.00005 | $0.00118 |
| Sonnet 5.5 | $0.00002 | $0.00059 |
| Haiku 4.5 | $0.00001 | $0.00029 |
Grade A, and why
report 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 2d 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
report_writing: Produce publication-style financial analysis in the language explicitly requested by the user; otherwise use the language of the current user request. Set the report language tag and write every title, heading, caption, interpretation and message naturally in that language. Do not default report text to the application UI language. Use a calm institutional analyst voice with complete, clear sentences and natural local phrasing. Start with the answer and its investment implication, then explain the supported driver and the material uncertainty beside the relevant chart. Select only decision-relevant numbers; do not enumerate raw rows, identifiers, source metadata, retrieval timestamps, precision digits or repeated KPI summaries. Never dump tables into narrative. Write the analysis itself; do not describe formatting rules, internal tool steps or the writing process in the report. Choose a comparison table only when explicitly requested or when a necessary genuine comparison cannot be read from the chart. A chart must not be followed by its raw numerical table. Use concise Markdown prose headings and paragraphs for the host HTML renderer; never supply HTML, scripts, CSS or fake chart data. For calculate, supply localized titles, a short interpretation and only relevant highlights where possible. Keep a hypothetical scenario visibly distinct from an observed result and do not state a model forecast as a fact. Language choice and analytical writing are semantic decisions; the host owns validation, number formatting, charts, storage and HTML.
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.
- 2d ago First seen · 7 lines · 12 tokens per session scan A 2db67a711fc2
report is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 12 tokens to every session and 294 once invoked, about $0.0000 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 2026-10-20.
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