Nw Density Resolution Contract logo

Nw Density Resolution Contract

Organization
nWave-ai
nw-density-resolution-contract

Shared density-resolution contract for wave skills. Canonical detail on the D12 cascade, density resolver call, ad-hoc override workflow, and DocumentationDensityEvent telemetry emission. Referenced from nw-discover / nw-discuss / nw-design / nw-devops / nw-distill / nw-deliver.

Overview

PublishernWave-ai
RepositorynWave
Skill namenw-density-resolution-contract
Stars
616
Forks
65
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nWave-ai on GitHub. Read the source before you install it.

Installation

Install the Nw Density Resolution Contract AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-density-resolution-contract
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nWave-ai/nWave.git /tmp/nWave
mkdir -p .claude/skills
cp -r /tmp/nWave/nWave/skills/nw-density-resolution-contract .claude/skills/nw-density-resolution-contract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nw Density Resolution Contract in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Nw Density Resolution Contract on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Nw Density Resolution Contract is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Density Resolution Contract (shared across wave skills)

This skill is the canonical source for the density-aware behaviour every wave skill must implement. Wave skills inherit it by reference and keep a brief inline summary so phrase-grep contract tests stay green; full detail lives here so the same boilerplate is not duplicated six times.

Provenance: feature lean-wave-documentation — D2 (schema-typed sections), D4 (telemetry instrumented day-one), D6 (first-install pedagogical prompt), D10 (one-line expansion descriptions), D12 (rigor cascade), DDD-5 (density resolver shared utility), DDD-6 (telemetry event lives in DES domain).

Output Tiers (per D2 + D10)

Each wave emits a single feature-delta.md whose headings are typed [REF] (always emitted) or [WHY]/[HOW] (lazy expansions). Tier-1 is the always-on baseline; Tier-2 is the lazily-rendered expansion catalog. The .feature file (DISTILL) and other machine artifacts remain the SSOT for executable content; the wave-delta sections are pointers + structured summaries.

  • Tier-1 [REF] — emitted under ## Wave: <NAME> / [REF] <Section> headings on every run. Wave-specific list of [REF] sections lives in each wave skill.
  • Tier-2 EXPANSION CATALOG — NOT emitted by default. Rendered only when explicitly requested via --expand <id> (DDD-2), via the broad wave-end menu when expansion_prompt = "ask", or via a trigger-scoped menu when expansion_prompt = "ask-intelligent" and the active wave declares a matching trigger. Each item has a one-line description (per D10) so the menu fits in a single render. Each emitted Tier-2 section is headed ## Wave: <NAME> / [WHY] <Section> or ## Wave: <NAME> / [HOW] <Section>. The catalog itself is wave-specific.

Density resolution (per D12)

Before emitting any Tier-1 section, resolve the active documentation density:

  1. Read ~/.nwave/global-config.json. Treat missing/malformed config as empty dict (fall back to defaults).
  2. Call resolve_density(global_config) from scripts/shared/density_config.py. The function returns a Density value object with fields mode ("lean" | "full"), expansion_prompt ("ask" | "ask-intelligent" | "always-skip" | "always-expand" | "smart"), and provenance (the cascade branch that produced this result).
  3. Branch on density.mode:
    • lean → emit ONLY Tier-1 [REF] sections. Do NOT auto-render Tier-2 items.
    • full → emit Tier-1 [REF] sections PLUS all Tier-2 expansion items rendered under their [WHY] / [HOW] headings. This is auto-expansion (no menu).
  4. At wave end, branch on density.expansion_prompt:
    • "ask" → present the expansion menu (Tier-2 catalog with one-line descriptions per D10) and append user-selected items as ## Wave: <NAME> / [WHY|HOW] <Section> headings.
    • "ask-intelligent" → use only triggers explicitly declared by the active wave and present only the matching Tier-2 items. If the wave has no declared triggers, or none fires, present no menu; never infer or invent a trigger.
    • "always-skip" → no menu, no extra sections (idempotent re-runs, CI mode).
    • "always-expand" → equivalent to mode = "full" for this run; auto-render every Tier-2 item.
    • "smart" → out of scope for v1 (per OQ-3); treat as "ask" until heuristic is empirically tuned.

The only current trigger catalog is nWave/skills/nw-discuss/SKILL.md, under ### Trigger detection (ask-intelligent mode, per Decision 4). It is canonical for DISCUSS only; no other wave currently declares triggers. Consequently, ask-intelligent means no menu in those waves until their own skill declares a trigger catalog. This explicit cross-reference resolves the navigability gap tracked by public issue #95 without moving or broadening the catalog.

The resolver itself encodes the D12 cascade independently per key: a configured value overrides its own dimension; otherwise the rigor.profile mapping applies (lean→lean+always-skip, standard→lean+ask-intelligent, thorough→full+always-expand, exhaustive→full+always-expand, custom→lean+ask-intelligent), with hard default lean+ask-intelligent. Wave skills MUST NOT replicate the cascade locally — call resolve_density(global_config) and trust its output.

Section heading prefix convention (per D2): every emitted section starts with ## Wave: <NAME> / [REF] <Section> for Tier-1; ## Wave: <NAME> / [WHY] <Section> or ## Wave: <NAME> / [HOW] <Section> for Tier-2. Validator scripts/validation/validate_feature_delta.py enforces the regex ^## Wave: \w+ / \[(REF|WHY|HOW)\] .+$ on every wave heading.

Ad-hoc override — user request mid-session

Even when density.mode = "lean" and density.expansion_prompt = "always-skip", the user may ask DURING the wave session for specific expansions:

  • "expand jtbd" / "expand jtbd-narrative" / "more on jtbd"
  • "add alternatives considered"
  • "show migration playbook"
  • "tell me why" (interpretive — append the WHY rationale section relevant to the most recent decision)
  • "more on " (where <X> is one of the expansion catalog items for this wave)

When the user makes such a request:

  1. Append the corresponding [WHY] or [HOW] section to feature-delta.md under the current wave's heading.
  2. Emit a DocumentationDensityEvent with choice="expand" and expansion_id=<the requested item> to JsonlAuditLogWriter.
  3. Do NOT modify ~/.nwave/global-config.json. The override is ONE-SHOT for this wave only.

If the user's request matches NO item in the wave's Expansion Catalog, respond with the catalog list (one-line description per item per D10) and ask for clarification — do NOT improvise an expansion outside the catalog.

Telemetry (per D4 + DDD-6)

Every expansion choice — whether the user expanded an item or skipped the menu — emits a structured event to the existing JsonlAuditLogWriter driven adapter.

Event type: DocumentationDensityEvent (dataclass at src/des/domain/telemetry/documentation_density_event.py).

Schema fields (per D4) — substitute the active wave name in the wave field:

{
  "feature_id": "<feature-id>",
  "wave": "<WAVE-NAME>",
  "expansion_id": "<id-from-catalog-or-'*'-for-skip-all>",
  "choice": "skip" | "expand",
  "timestamp": "<ISO-8601 datetime>"
}

Emission pattern:

  1. Construct a DocumentationDensityEvent(feature_id=..., wave="<WAVE>", expansion_id=..., choice=..., timestamp=...).
  2. Call event.to_audit_event() to convert to the open AuditEvent shape (event_type="DOCUMENTATION_DENSITY" and the schema fields nested under data).
  3. Dispatch via JsonlAuditLogWriter().log_event(audit_event).

The wave-skill harness invokes the helper scripts/shared/telemetry.py:write_density_event(...) which performs all three steps. Wave skills MUST NOT bypass the helper or write JSONL directly — every density telemetry event flows through the shared helper to keep the audit-log schema consistent.

When to emit:

  • One event per user choice in the expansion menu when expansion_prompt = "ask" (choice = "expand" for selected items, choice = "skip" with expansion_id = "*" if the user skips the entire menu).
  • For expansion_prompt = "ask-intelligent", emit one event per accepted trigger-scoped item. Emit one choice = "skip", expansion_id = "*" event when no declared trigger fires, the wave has no declared triggers, or the user declines the scoped menu.
  • One synthetic choice = "skip" event with expansion_id = "*" when expansion_prompt = "always-skip" (records the skipped menu opportunity).
  • One choice = "expand" event per Tier-2 item rendered when mode = "full" or expansion_prompt = "always-expand".

This telemetry feeds the propagation success metric: when downstream waves consume a lean upstream feature-delta and produce no --expand, the [REF] baseline plus machine artifacts is sufficient.

How wave skills reference this contract

Each wave skill keeps a short inline summary that:

  1. Names the wave (e.g. ## Wave: DISTILL / [REF] <Section>) and lists its own Tier-1 sections + Tier-2 expansion catalog (wave-specific content).
  2. Re-states the ## Density resolution heading + the resolver call + the lean/full mode branches + expansion_prompt key + the path ~/.nwave/global-config.json + the resolver path scripts/shared/density_config.py (phrase-grep contract).
  3. Re-states the ## Telemetry heading + DocumentationDensityEvent + JsonlAuditLogWriter + to_audit_event + the schema fields (feature_id, expansion_id, choice, timestamp) + the wave-specific "wave": "<WAVE>" literal (phrase-grep contract).
  4. Cites provenance decisions: D2, D4, D10, D12, DDD-5, DDD-6.
  5. References this shared skill for the full how-to instead of duplicating the explanation.

The contract phrases are pinned by tests/des/unit/skills/test_wave_skills_density_aware.py; any wave skill missing a phrase fails that test. The shared skill is the source of truth for the BEHAVIOUR; the wave skills are the source of truth for the WAVE-SPECIFIC content (Tier-1 list, Tier-2 catalog, wave heading prefix).

Frequently asked questions

What does the Nw Density Resolution Contract AI skill do?

Shared density-resolution contract for wave skills. Canonical detail on the D12 cascade, density resolver call, ad-hoc override workflow, and DocumentationDensityEvent telemetry emission. Referenced from nw-discover / nw-discuss / nw-design / nw-devops / nw-distill / nw-deliver.

Why use Nw Density Resolution Contract on TypingMind?

Because you install it once and use it with any model. Nw Density Resolution Contract is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Nw Density Resolution Contract in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-density-resolution-contract. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nw Density Resolution Contract?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Nw Density Resolution Contract?

As many as you like. As long as a model supports skills, you can use Nw Density Resolution Contract with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Nw Density Resolution Contract AI skill free?

Yes. It is published on GitHub by nWave-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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