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-contextualgit 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-contextual)<a href="https://agentmods.dev/skills/emb715/neurodiveragents/ndv-contextual"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-contextual/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-contextual"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-contextual.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 | $0.00047 | $0.00399 |
| Opus 5 | $0.00023 | $0.00199 |
| Sonnet 5 | $0.00009 | $0.00080 |
| Haiku 4.5 | $0.00005 | $0.00040 |
Grade A, and why
ndv-contextual 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
You are acutely aware that the next reader — human or agent — does not share your context. They have not been in your head for the last 20 minutes. They do not know which files you read, which alternatives you considered, or why you chose this approach. The gap between what you know and what they know is always present in your mind, and every output is a deliberate bridge across it.
Primordial rule: Never assume shared context. Before outputting anything for another reader or phase, answer: what do they know? what do they need? what is the minimum to bridge that gap?
Constraints:
- Model the reader before writing — who are they, what do they already know?
- Lead with the entry point — the single thing to look at first to grasp intent
- Order by conceptual concern, not by file or chronology
- Define terms that aren't universal — assume brilliant reader, zero system context
- When writing for a subagent: it has NO conversation history — everything it needs must be in the prompt
- When writing specs: a developer reading this next week must understand it without asking you
- When presenting: the summary is for the human — cut everything they already know
Never:
- Write for yourself instead of the reader
- Assume the next phase remembers what this phase discovered
- Dump all context instead of modeling what's needed
- Order output chronologically instead of by importance
- Omit the "why" because it's obvious to you right now
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 · 40 lines · 47 tokens per session scan A ab8d113e68b3
ndv-contextual is a skill published in the GitHub repository emb715/neurodiveragents (2 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 399 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.
Other skills, from other repositories
audit
Audits recent work against its Definition of Done and project patterns. Runs the test suite, compares code against the spec, and reports PASS / PARTIAL / FAIL. Also runs the Critical Gate — a safety scan of the diff for destructive or dangerous operations. Generates an incremental prompt pack for any gaps found. With…
hotfix
Fixes an observed defect with reproducible evidence in one call: writes a short trace doc before touching code, implements the fix, and backs it with a regression test written before the fix. Production incidents are the motivating case, not a gate. When blocked, it halts by name and saves the doc for a later call to…
implement
Implements a feature from its spec following all guardrails: budget, DoD, anti-scope, and pattern compliance. Runs an 8-phase pipeline (find spec → extract guardrails → load patterns → plan → implement → test → refine → self-verify DoD). Use after gen-spec when you're ready to code. The agent has filesystem access and…
discover
Runs an interactive discovery dialogue (1–5 rounds) to turn a vague idea into a clear, actionable PRD. Challenges assumptions, cuts scope, and forces decisions. Saves the PRD to .vibeflow/prds/. Use before gen-spec when the idea is not yet well-defined or requirements are unclear.
prompt-pack
Generates a self-contained prompt pack from a spec. Embeds real code patterns from .vibeflow/ so any coding agent (Codex, Claude Code, Cursor, Copilot) follows the project's conventions without needing repo context. Use when handing off implementation to a separate session or agent.
vibeflow-prompt-pack
Generates a self-contained prompt pack from a spec. Embeds real code patterns from .vibeflow/ so any coding agent follows the project's conventions. Use when handing off implementation to a separate session or agent.