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 hyxnj666-creator/ai-memory --skill ai-memory-coding-conventionsgit clone --depth 1 https://github.com/hyxnj666-creator/ai-memoryWrote 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/hyxnj666-creator/ai-memory/ai-memory-coding-conventions)<a href="https://agentmods.dev/skills/hyxnj666-creator/ai-memory/ai-memory-coding-conventions"><img src="https://agentmods.dev/badge/skills/hyxnj666-creator/ai-memory/ai-memory-coding-conventions.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.00266 |
| Opus 5 | $0.00023 | $0.00133 |
| Sonnet 5 | $0.00009 | $0.00053 |
| Haiku 4.5 | $0.00005 | $0.00027 |
Grade A, and why
ai-memory-coding-conventions 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 8d 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
Coding Conventions
Auto-generated by ai-memory from AI chat history. Edit memories via
ai-memory list/extract/resolverather than this file — it is fully regenerated on everyai-memory rules --target skills.
Cursor pagination is mandatory for all paged GraphQL endpoints
Every paged GraphQL endpoint MUST use Relay-style cursor pagination (edges / node / cursor + pageInfo.hasNextPage). Choose first + after as the canonical pair; reject last + before unless explicitly justified per endpoint. CI lint rule will enforce on new schema.
Why: Cursor pagination is stable across mutations and aligns with the Apollo/Relay tooling already in use. Migration of existing offset endpoints exposes both shapes for one minor version so consumers can switch over without breakage.
Rejected: Offset/limit (rejected, see Context). Page-token-only (rejected — no cursor opacity guarantee, leaks server state). Custom cursor scheme (rejected — no benefit over Relay spec).
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.
- 8d ago First seen · 17 lines · 46 tokens per session scan A 6d498bd7a619
ai-memory-coding-conventions is a skill published in the GitHub repository hyxnj666-creator/ai-memory (43 stars, last pushed 4mo ago), licensed MIT. It adds 46 tokens to every session and 266 once invoked, about $0.0002 per session on Opus 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 2026-08-30.
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