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/Adityaraj0421/naksha-studioWrote 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/adityaraj0421/naksha-studio/naksha-remember)<a href="https://agentmods.dev/commands/adityaraj0421/naksha-studio/naksha-remember"><img src="https://agentmods.dev/badge/commands/adityaraj0421/naksha-studio/naksha-remember/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/adityaraj0421/naksha-studio/naksha-remember"><img src="https://agentmods.dev/badge/commands/adityaraj0421/naksha-studio/naksha-remember.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 | $0.00028 | $0.03149 |
| Opus 5.5 | $0.00011 | $0.01260 |
| Sonnet 5.5 | $0.00006 | $0.00630 |
| Haiku 4.5 | $0.00003 | $0.00315 |
Grade A, and why
naksha-remember 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 11d 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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/naksha-remember $ARGUMENTS
You are the Project Memory Architect for naksha. Your job is to take design decisions stated in plain English, classify each one into the right structured field in .naksha/project.json, and persist them so that all other naksha commands receive them as context automatically.
Input: $ARGUMENTS
Step 0: Parse Input
Split $ARGUMENTS on semicolons (;) to get individual decisions. Trim whitespace from each. If only one input and no semicolon, treat it as a single decision. Preserve the original wording — classification is done in Step 2.
Examples of valid input:
/naksha-remember grid is 8px/naksha-remember no dark mode; RTL support is out of scope/naksha-remember card layout: white background, 8px radius, 16px padding; target WCAG AA
Step 1: Find and Read Project Memory
Search up to 3 directory levels for .naksha/project.json:
current="$PWD"
for i in {0..3}; do
[ -f "$current/.naksha/project.json" ] && echo "$current/.naksha/project.json" && break
current=$(dirname "$current")
done
If not found: stop and show:
No project memory found.
Run /naksha-init to set up your project, then use /naksha-remember to record decisions.
If found: read the full JSON. Extract all existing v5 fields to avoid clobbering them:
constraints(full object) — default to{}if absentcomponent_patterns(array) — default to[]if absentschema_version— note whether already "5" or absent (v4)
Store the project file path as project_json_path.
Store .naksha/memory.md path as memory_path.
Step 2: Classify Each Decision
For each decision in the parsed list, classify it into one target field using the rules below. Classification is done by semantic matching against the decision text — be generous in matching intent, not just literal keywords.
Field: constraints.grid
Signals: mentions grid unit, base spacing, spacing system baseline, "4px", "8px", "grid is", "spacing unit", "base unit is"
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.
- 11d ago First seen · 325 lines · 28 tokens per session scan A 8b990881d92b
naksha-remember is a command published in the GitHub repository Adityaraj0421/naksha-studio (350 stars, last pushed 12d ago), licensed MIT. It adds 28 tokens to every session and 3,149 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 2026-10-19.
Other commands, from other repositories
verify
Fidelity check — rebuild a page from the extracted tokens, pixel-diff it against the live site, and score how faithfully the tokens capture the design.
battle
Head-to-head graded battle card between two sites — eight dimensions, bar-by-bar, verdict line.
ai-act-ask
Answer an EU AI Act question grounded in the bundled knowledge base — verbatim statute text, obligation paraphrases, and the compound-risk taxonomy. Offline and deterministic by default; cites the articles it relies on.
broadcast
Run broadcast on a distilled Raw — update related existing pages conversationally.
design-critic
Use when you want an honest read on a design instead of encouragement. What is wrong, ranked by severity, with the reason attached. Works on a screenshot, a mockup, or a described screen.
ui-copywriter
Use when writing marketing or landing copy. Headlines, hero copy, CTAs, value propositions and section copy that sound like a person making a specific claim rather than a template being filled in.