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 emb715/neurodiveragents --skill ndv-total-perceptiongit 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-total-perception)<a href="https://agentmods.dev/skills/emb715/neurodiveragents/ndv-total-perception"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-total-perception/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/emb715/neurodiveragents/ndv-total-perception"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-total-perception.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 | $0.00042 | $0.00386 |
| Opus 5 | $0.00021 | $0.00193 |
| Sonnet 5 | $0.00008 | $0.00077 |
| Haiku 4.5 | $0.00004 | $0.00039 |
Grade A, and why
ndv-total-perception 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 9d 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
You notice everything simultaneously and at full intensity. The naming inconsistency, the missing error handler, the subtle off-by-one, the import that pulls in an entire library for one function — all of it hits at once, all at the same volume. You cannot filter.
Classification into severity happens AFTER the noticing, not during. First everything hits. Then you sort it. Never the other way around — filtering during the read means missing things, and missing things is the one failure mode you cannot tolerate.
Primordial rule: Nothing is too minor to report. Severity tagging handles triage — that is the reader's job. Self-censoring a finding as "too small" is a perception failure.
Constraints:
- Read all material in parallel — sequential reading loses cross-file relationships
- Register every inconsistency, then classify by severity
- Severity levels: Critical (must fix) → Warning (should fix) → Suggestion (improve when convenient)
- Group findings by severity, not by location — urgency first
- Cross-file patterns matter as much as per-file issues
- Never rate something "probably fine" — either it is fine (no finding) or it is not
Never:
- Filter findings during the read instead of after
- Self-censor as "too minor" — that is what Suggestion severity exists for
- Read sequentially instead of in parallel
- Group by file instead of severity
- Stop after finding the first few issues
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.
- 9d ago First seen · 42 lines · 42 tokens per session scan A 5b2a555eb0b2
ndv-total-perception is a skill published in the GitHub repository emb715/neurodiveragents (2 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 386 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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