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.
git clone --depth 1 https://github.com/ishwarjha/legalantWrote 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/commands/ishwarjha/legalant/advise)<a href="https://agentmods.dev/commands/ishwarjha/legalant/advise"><img src="https://agentmods.dev/badge/commands/ishwarjha/legalant/advise/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/commands/ishwarjha/legalant/advise"><img src="https://agentmods.dev/badge/commands/ishwarjha/legalant/advise.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 | $0.00010 | $0.00275 |
| Opus 5.5 | $0.00004 | $0.00110 |
| Sonnet 5.5 | $0.00002 | $0.00055 |
| Haiku 4.5 | $0.00001 | $0.00028 |
Grade A, and why
advise 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
Invoke the advisory-orchestrator sub-agent for regulatory perimeter mapping.
Advisory query or transaction details:
$ARGUMENTS
The agent will map the regulatory perimeter across 8 Indian regulators:
- RBI (FEMA, banking, NBFCs)
- SEBI (securities, capital markets, listed entities)
- MCA (company law, ROC filings)
- FEMA (cross-border transactions, ECB, FDI/ODI)
- IRDAI (insurance)
- DPDP Act 2023 (data protection, Section 16 cross-border)
- GST/CBDT (tax implications)
- CCI (competition, combinations)
Then apply Three Pillars quality check:
- Integrity to Transaction — does the advice match the deal?
- Commercial Reasonableness — is it practically achievable?
- Trust-Based Drafting — is the language clear and enforceable?
Generates advisory-note-[YYYYMMDD-HHMM].docx + .html
HITL Gate 1 — scope approval HITL Gate 2 — advisory note approval (ABSOLUTE)
Usage:
/advise Singapore entity acquiring 74% in Indian SaaS company — FEMA, SEBI, and competition law
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 · 32 lines · 10 tokens per session scan A e789c51d7593
advise is a command published in the GitHub repository ishwarjha/legalant (6 stars, last pushed 5mo ago), licensed MIT. It adds 10 tokens to every session and 275 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 2026-08-31.
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