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/nWave-ai/nWaveWrote 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/nwave-ai/nwave/discuss)<a href="https://agentmods.dev/commands/nwave-ai/nwave/discuss"><img src="https://agentmods.dev/badge/commands/nwave-ai/nwave/discuss/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/nwave-ai/nwave/discuss"><img src="https://agentmods.dev/badge/commands/nwave-ai/nwave/discuss.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 | $0.00035 | $0.02877 |
| Opus 5.5 | $0.00014 | $0.01151 |
| Sonnet 5.5 | $0.00007 | $0.00575 |
| Haiku 4.5 | $0.00003 | $0.00288 |
Grade A, and why
discuss 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 1mo 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NW-DISCUSS: Jobs-to-be-Done Analysis, UX Journey Design, and Requirements Gathering
Wave: DISCUSS (wave 2 of 6) | Agent: Luna (nw-product-owner) | Command: /nw-discuss
Overview
Execute DISCUSS wave through Luna's integrated workflow: JTBD analysis|UX journey discovery|emotional arc design|shared artifact tracking|requirements gathering|user story creation|acceptance criteria definition. Luna uncovers jobs users accomplish, maps to journeys and requirements, handles complete lifecycle from user motivations through DoR-validated stories ready for DESIGN. Establishes ATDD foundation.
For greenfield projects (no src/ code, no docs/feature/ history), Luna proposes Walking Skeleton as Feature 0.
Interactive Decision Points
Decision 1: Feature Type
Question: What type of feature is this? Options:
- User-facing -- UI/UX functionality visible to end users
- Backend -- APIs, services, data processing
- Infrastructure -- DevOps, CI/CD, tooling
- Cross-cutting -- Spans multiple layers (auth, logging, etc.)
- Other -- user provides custom input
Decision 2: Walking Skeleton
Question: Should we start with a walking skeleton? Options:
- Yes -- recommended for greenfield projects
- Depends -- brownfield; Luna evaluates existing structure first
- No -- feature is isolated enough to skip
Decision 3: UX Research Depth
Question: Priority for UX research depth? Options:
- Lightweight -- quick journey map, focus on happy path
- Comprehensive -- full experience mapping with emotional arcs
- Deep-dive -- extensive user research, multiple personas, edge cases
Prior Wave Consultation
Before beginning DISCUSS work, read SSOT and prior wave artifacts:
- SSOT (if
docs/product/exists):docs/product/journeys/{name}.yaml— existing journey to extend (if applicable)docs/product/jobs.yaml— validated jobs and opportunity scoresdocs/product/vision.md— product vision
- Project context:
docs/project-brief.md|docs/stakeholders.yaml - DISCOVER artifacts: Read
docs/feature/{feature-id}/discover/(if present) - DIVERGE artifacts: Read
docs/feature/{feature-id}/diverge/(if present)recommendation.mdis the primary input — the selected design direction and job statementjob-analysis.md— validated JTBD job statements and ODI outcome statements — use directly, do not re-run JTBD analysis
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.
- 1mo ago First seen · 240 lines · 35 tokens per session scan A 6832b56a5fa7
discuss is a command published in the GitHub repository nWave-ai/nWave (621 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 2,877 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 2026-09-06.
Other commands, from other repositories
implement
Execute tasks from a track's implementation plan following TDD workflow.
status
Display project status, active tracks, and next actions.
portfolio
Show a read-only hub-wide portfolio of canonical Ideas and active Projects without duplicating topic-owned records.
amend-plan
Plan Amend - Discuss and apply amendments to a plan.json implementation plan.
dashboard-session-fork
Fork a session into a new one. Usage /dashboard:session-fork.
dashboard-session-hide
Hide a session from the dashboard list. Usage /dashboard:session-hide.