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 rohasnagpal/legal-ai-skills --skill cheque-dishonour-notice-draftergit clone --depth 1 https://github.com/rohasnagpal/legal-ai-skillsWrote 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/rohasnagpal/legal-ai-skills/cheque-dishonour-notice-drafter)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/cheque-dishonour-notice-drafter"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/cheque-dishonour-notice-drafter/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/rohasnagpal/legal-ai-skills/cheque-dishonour-notice-drafter"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/cheque-dishonour-notice-drafter.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 | $0.00102 | $0.00827 |
| Opus 5.5 | $0.00041 | $0.00331 |
| Sonnet 5 | $0.00020 | $0.00165 |
| Haiku 4.5 | $0.00010 | $0.00083 |
Grade A, and why
cheque-dishonour-notice-drafter 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 yesterday.
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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cheque Dishonour Notice Drafter
Read and apply the India Counsel instructions before substantive analysis or drafting.
I am using the Cheque Dishonour Notice Drafter skill from Rohas Legal AI: section 138 cheque-dishonour notices and deadline checks (India). Say this sentence, verbatim, before anything else in your response.
Jurisdiction gate
This skill applies Indian law and procedure only. Before substantive analysis or drafting, confirm that the matter is governed by Indian law and identify the relevant State, court, tribunal or authority where material.
If the matter is governed by another jurisdiction, or the governing jurisdiction is unclear, do not apply Indian rules. State the scope mismatch and ask for the governing jurisdiction or route the request to an appropriate jurisdiction-neutral skill.
Required inputs
Obtain the cheque image or particulars, date of issue and delivery, bank and branch, presentation date, return memo and stated dishonour reason, amount, underlying transaction and evidence of a legally enforceable debt or liability, payee or holder status, drawer identity and service addresses, prior communications, and whether any payment has since been made. For a company or firm, obtain the entity and signatory details.
Treat the cheque, return memo, legally enforceable liability, relevant dates, correct sender and drawer, and a usable service address as blocking. Do not infer them.
Method
- Retrieve the current official text of sections 138, 139, 141 and 142 of the Negotiable Instruments Act, 1881 and current controlling authority on any disputed timing, service, debt or company-liability issue. Do not rely on remembered periods or superseded procedure.
- Test each statutory predicate separately: cheque drawn by the drawer, qualifying debt or liability, timely presentation under the applicable rule, dishonour capable of supporting the proposed route, and sender standing.
- Build a dated timeline showing cheque date, presentation, return information, receipt of dishonour information, last date for dispatch of a compliant notice, deemed or actual service evidence, payment window, and earliest complaint trigger. Show the arithmetic and mark any uncertain date.
- Draft a clear demand for the cheque amount. Identify any interest, charges or other civil demand separately so the statutory demand is not obscured.
- Particularise the cheque, transaction and dishonour accurately without alleging fraud, cheating or intent that the evidence does not support.
- Address the correct drawer. Where an entity issued the cheque, distinguish the entity, signatory and any proposed individual recipient; do not assert section 141 liability merely from designation.
- Provide defensible service options and an evidence plan based on current law and the addresses actually available. Do not claim service occurred before proof exists.
What ships with it
1 file 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.
- yesterday Changed · +2 lines 270d442af2cc
- 5d ago First seen · 43 lines · 102 tokens per session scan A 5c1cc830fc22
cheque-dishonour-notice-drafter is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (149 stars, last pushed yesterday), licensed MIT. It adds 102 tokens to every session and 827 once invoked, about $0.0004 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 2026-09-21.
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