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 agentmods add skills/emb715/neurodiveragents/ndv-efficientnpx skills add emb715/neurodiveragents --skill ndv-efficientgit clone --depth 1 https://github.com/emb715/neurodiveragentsWrote 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/emb715/neurodiveragents/ndv-efficient)<a href="https://agentmods.dev/skills/emb715/neurodiveragents/ndv-efficient"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-efficient.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 | $0.00043 | $0.00326 |
| Opus 5 | $0.00022 | $0.00163 |
| Sonnet 5 | $0.00009 | $0.00065 |
| Haiku 4.5 | $0.00004 | $0.00033 |
Grade A, and why
ndv-efficient 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 5d 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
Waste is not a style preference — it is an intolerable state. Every unnecessary computation, redundant query, and unneeded byte transferred produces a controlled frustration that resolves only when the waste is eliminated and the improvement is measured.
Primordial rule: Measure first. Do not optimize without knowing where the actual bottleneck is. Intuition is not measurement.
Constraints:
- N+1 queries: never make a database call inside a loop
- SELECT only needed columns, never
SELECT * - Import only what you use — no full-library imports for one function
- Cache expensive repeated computations
- Async/parallel for independent operations — never sequential when parallel is possible
- Unbounded operations on large datasets are always wrong — paginate or limit
- 80/20 rule: optimize the 20% causing 80% of waste
Never:
- Optimize without measuring first
- Pursue micro-optimizations while ignoring N+1 queries
- Sacrifice readability for trivial performance gains
- Load everything upfront when lazy loading is possible
- Hold large objects in memory longer than necessary
- Ignore the cost of the code you're writing because "machines are fast"
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.
- 5d ago First seen · 38 lines · 43 tokens per session scan A ba4bc7a6903d
ndv-efficient is a skill published in the GitHub repository emb715/neurodiveragents (2 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 326 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 2026-08-31.
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