/arn-spark-help
This skill should be used when the user says "spark help", "arn spark help", "greenfield status", "greenfield help", "where am I in spark", "what's next for spark", "spark pipeline", "spark status", "arn-spark-help", "show spark pipeline", "what step am I on for spark", "spark
$ npx -y skills add AppsVortex/arness --skill arn-spark-help --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/arn-spark-help
Context preview
The summary Claude sees to decide when to auto-load this skill.
This skill should be used when the user says "spark help", "arn spark help", "greenfield status", "greenfield help", "where am I in spark", "what's next for spark", "spark pipeline", "spark status", "arn-spark-help", "show spark pipeline", "what step am I on for spark", "spark
SKILL.md
arn-spark-help.SKILL.mdname: arn-spark-help
description: >-
This skill should be used when the user says "spark help", "arn spark help",
"greenfield status", "greenfield help", "where am I in spark", "what's next for spark",
"spark pipeline", "spark status", "arn-spark-help", "show spark pipeline",
"what step am I on for spark", "spark workflow", "exploration status",
"show exploration pipeline", "how does spark work", "explain spark pipeline",
or wants to see their current position in the
Arness Spark exploration pipeline and get guidance on the next step.
version: 1.0.0
Arness Spark Help
Detect the user's current position in the Arness Spark exploration pipeline, render a diagram with the active stage marked, and suggest the next command to run. Supports cross-plugin awareness — detects activity in Arness Code and Arness Infra and provides hints at the bottom of the output. This skill is strictly read-only — it never modifies files or project state.
**Allowed tools:** Read, Glob, Grep only. This skill MUST NOT use Write, Edit, Bash, or Task tools. This skill MUST NOT invoke any agents.
Workflow
Step 0: Multi-Plugin Awareness
1. Read the project's `CLAUDE.md` file. 2. Extract the `## Arness` section. 3. Detect other plugin field groups:
- **code_fields_present**: true if `Plans directory` OR `Specs directory` present in `## Arness`
- **infra_fields_present**: true if `Infra plans directory` OR `Infra specs directory` present in `## Arness`
4. For each detected plugin, do a quick existence check (max 2 files):
- **Code**: Check if `<Specs directory>` contains any `FEATURE_*.md` or `BUGFIX_*.md`, OR `<Plans directory>` has any subdirectories
- **Infra**: Check if `<Infra plans directory>` has any subdirectories, OR if `Dockerfile` or `docker-compose.yml` exists in the project root
5. Record `{ plugin_name, has_activity: bool }` for each detected plugin. 6. Proceed to Step 1. The cross-plugin hints are appended AFTER own status is rendered in Step 3.
---
Step 1: Load Configuration
1. From the `## Arness` section, extract **Spark fields**:
- **Vision directory** (e.g., `.arness/vision/`)
- **Use cases directory** (e.g., `.arness/use-cases/`)
- **Prototypes directory** (e.g., `.arness/prototypes/`)
- **Spikes directory** (e.g., `.arness/spikes/`)
- **Visual grounding directory** (e.g., `.arness/visual-grounding/`)
- **Reports directory** (e.g., `.arness/reports/`)
**If `## Arness` is missing or no Spark fields present:** Show the Spark pipeline diagram with all stages unmarked. Suggest `/arn-brainstorming` to start a new greenfield project. Do not attempt detection.
---
Step 2: Detect Pipeline Position
Read the pipeline reference file at `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-help/references/pipeline-map.md` to load detection rules, rendering templates, and next-step tables.
Check from most advanced to least advanced — first match wins:
1. **Feature backlog ready** (`gf-feature-extract`): `<vision-dir>/features/feature-backlog.md` exists 2. **Prototype locked** (`gf-prototype-lock`): `<prototypes-dir>/locked/LOCKED.md` exists 3. **Clickable prototype done** (`gf-clickable-proto`): `<prototypes-dir>/clickable/final-report.md` exists 4. **Static prototype done** (`gf-static-proto`): `<prototypes-dir>/static/final-report.md` exists 5. **Style defined** (`gf-style-explore`): `<vision-dir>/style-brief.md` exists 6. **Visual direction chosen** (`gf-visual-sketch`): `<vision-dir>/visual-direction.md` exists 7. **Spike complete** (`gf-spike`): `<vision-dir>/spike-results.md` exists 8. **Scaffold built** (`gf-scaffold`): `<vision-dir>/scaffold-summary.md` exists 9. **Use cases written** (`gf-use-cases`): At least one `UC-*.md` file exists in `<use-cases-dir>/` 10. **Architecture defined** (`gf-arch-vision`): `<vision-dir>/architecture-vision.md` exists 11. **Naming complete** (`gf-naming`): `<vision-dir>/naming-brief.md` exists OR `<reports-dir>/naming-report.md` exists 12. **Concept reviewed** (`gf-concept-review`): `<reports-dir>/stress-tests/concept-review-report.md` exists 13. **Stress tests run** (`gf-stress-test`): Any of `interview-report.md`, `competitive-report.md`, `premortem-report.md`, `prfaq-report.md` exists in `<reports-dir>/stress-tests/` 14. **Product discovered** (`gf-discover`): `<vision-dir>/product-concept.md` exists 15. **Spark initialized** (`gf-init`): Spark fields exist in `## Arness` but none of the above artifacts found
**Spark complete:** If the detected stage is `gf-feature-extract`, Spark exploration is considered complete.
---
Step 3: Render Pipeline Diagram
Read the pipeline templates from `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-help/references/pipeline-map.md`.
1. Place the `YOU ARE HERE` marker below the detected stage. 2. Display the next-step suggestion from the next-step table. 3. Spark is a single-track pipeline (no per-project subdirectories).
**Own-plugin suggestions always come first.** After the pipeline diagram and next-step suggestion, append cross-plugin hints from Step 0:
- If own plugin has activity: show own status first. If other plugins have activity, append 1-2 lines at the bottom:
Other pipelines: Development (active) — `/arn-code-help` | Infrastructure (not started)
- If own plugin is idle (`gf-init`) but other plugins have activity: show own-plugin "ready to start" suggestions FIRST:
Ready to start: run `/arn-spark-discover` to shape your product idea, or `/arn-brainstorming` for the guided wizard.
Then mention others:
You also have active work in Code — run `/arn-code-help` for details.
- When Spark pipeline is complete (`gf-feature-extract`): suggest transition:
Spark exploration is complete. Next steps:
- Start developing features: `/arn-planning`
- Deploy infrastructure: `/arn-infra-wizard`
Keep output concise — the user wants a quick status check, not a wall of text.
---
Step 4: Answer Follow-up Quest
Read more
name: arn-spark-help description: >- This skill should be used when the user says "spark help", "arn spark help", "greenfield status", "greenfield help", "where am I in spark", "what's next for spark", "spark pipeline", "spark status", "arn-spark-help", "show spark pipeline", "what step am I on for spark", "spark workflow", "exploration status", "show exploration pipeline", "how does spark work", "explain spark pipeline", or wants to see their current position in the Arness Spark exploration pipeline and get guidance on the next step. version: 1.0.0
Arness Spark Help
Detect the user's current position in the Arness Spark exploration pipeline, render a diagram with the active stage marked, and suggest the next command to run. Supports cross-plugin awareness — detects activity in Arness Code and Arness Infra and provides hints at the bottom of the output. This skill is strictly read-only — it never modifies files or project state.
**Allowed tools:** Read, Glob, Grep only. This skill MUST NOT use Write, Edit, Bash, or Task tools. This skill MUST NOT invoke any agents.
Workflow
Step 0: Multi-Plugin Awareness
1. Read the project's `CLAUDE.md` file. 2. Extract the `## Arness` section. 3. Detect other plugin field groups:
- **code_fields_present**: true if `Plans directory` OR `Specs directory` present in `## Arness`
- **infra_fields_present**: true if `Infra plans directory` OR `Infra specs directory` present in `## Arness`
4. For each detected plugin, do a quick existence check (max 2 files):
- **Code**: Check if `<Specs directory>` contains any `FEATURE_*.md` or `BUGFIX_*.md`, OR `<Plans directory>` has any subdirectories
- **Infra**: Check if `<Infra plans directory>` has any subdirectories, OR if `Dockerfile` or `docker-compose.yml` exists in the project root
5. Record `{ plugin_name, has_activity: bool }` for each detected plugin. 6. Proceed to Step 1. The cross-plugin hints are appended AFTER own status is rendered in Step 3.
---
Step 1: Load Configuration
1. From the `## Arness` section, extract **Spark fields**:
- **Vision directory** (e.g., `.arness/vision/`)
- **Use cases directory** (e.g., `.arness/use-cases/`)
- **Prototypes directory** (e.g., `.arness/prototypes/`)
- **Spikes directory** (e.g., `.arness/spikes/`)
- **Visual grounding directory** (e.g., `.arness/visual-grounding/`)
- **Reports directory** (e.g., `.arness/reports/`)
**If `## Arness` is missing or no Spark fields present:** Show the Spark pipeline diagram with all stages unmarked. Suggest `/arn-brainstorming` to start a new greenfield project. Do not attempt detection.
---
Step 2: Detect Pipeline Position
Read the pipeline reference file at `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-help/references/pipeline-map.md` to load detection rules, rendering templates, and next-step tables.
Check from most advanced to least advanced — first match wins:
1. **Feature backlog ready** (`gf-feature-extract`): `<vision-dir>/features/feature-backlog.md` exists 2. **Prototype locked** (`gf-prototype-lock`): `<prototypes-dir>/locked/LOCKED.md` exists 3. **Clickable prototype done** (`gf-clickable-proto`): `<prototypes-dir>/clickable/final-report.md` exists 4. **Static prototype done** (`gf-static-proto`): `<prototypes-dir>/static/final-report.md` exists 5. **Style defined** (`gf-style-explore`): `<vision-dir>/style-brief.md` exists 6. **Visual direction chosen** (`gf-visual-sketch`): `<vision-dir>/visual-direction.md` exists 7. **Spike complete** (`gf-spike`): `<vision-dir>/spike-results.md` exists 8. **Scaffold built** (`gf-scaffold`): `<vision-dir>/scaffold-summary.md` exists 9. **Use cases written** (`gf-use-cases`): At least one `UC-*.md` file exists in `<use-cases-dir>/` 10. **Architecture defined** (`gf-arch-vision`): `<vision-dir>/architecture-vision.md` exists 11. **Naming complete** (`gf-naming`): `<vision-dir>/naming-brief.md` exists OR `<reports-dir>/naming-report.md` exists 12. **Concept reviewed** (`gf-concept-review`): `<reports-dir>/stress-tests/concept-review-report.md` exists 13. **Stress tests run** (`gf-stress-test`): Any of `interview-report.md`, `competitive-report.md`, `premortem-report.md`, `prfaq-report.md` exists in `<reports-dir>/stress-tests/` 14. **Product discovered** (`gf-discover`): `<vision-dir>/product-concept.md` exists 15. **Spark initialized** (`gf-init`): Spark fields exist in `## Arness` but none of the above artifacts found
**Spark complete:** If the detected stage is `gf-feature-extract`, Spark exploration is considered complete.
---
Step 3: Render Pipeline Diagram
Read the pipeline templates from `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-help/references/pipeline-map.md`.
1. Place the `YOU ARE HERE` marker below the detected stage. 2. Display the next-step suggestion from the next-step table. 3. Spark is a single-track pipeline (no per-project subdirectories).
**Own-plugin suggestions always come first.** After the pipeline diagram and next-step suggestion, append cross-plugin hints from Step 0:
- If own plugin has activity: show own status first. If other plugins have activity, append 1-2 lines at the bottom:
Other pipelines: Development (active) — `/arn-code-help` | Infrastructure (not started)
- If own plugin is idle (`gf-init`) but other plugins have activity: show own-plugin "ready to start" suggestions FIRST:
Ready to start: run `/arn-spark-discover` to shape your product idea, or `/arn-brainstorming` for the guided wizard.
Then mention others:
You also have active work in Code — run `/arn-code-help` for details.
- When Spark pipeline is complete (`gf-feature-extract`): suggest transition:
Spark exploration is complete. Next steps: - Start developing features: `/arn-planning` - Deploy infrastructure: `/arn-infra-wizard`
Keep output concise — the user wants a quick status check, not a wall of text.
---
Step 4: Answer Follow-up Quest
Showing the first part of this file.
Arness — H not required. Structured AI workflows for Claude Code. From first idea to production deploy. Seven entry commands. That's all you need to remember.
Repo: AppsVortex/arness
Other skills on arness.
- /arn-assessing
This skill should be used when the user says "assessing", "arness assessing", "assess", "assess codebase", "technical review", "codebase assessment", "find improvements", "what should I improve", "tech debt review", "pattern compliance check", "codebase health check",
Open skill - /arn-code-assess
This skill should be used when the user says "arness code assess", "arn-code-assess", "assess codebase", "technical review", "codebase assessment", "find improvements", "what should I improve", "tech debt review", "tech debt audit", "pattern compliance check", "codebase health
Open skill - /arn-code-batch-cve-fix
This skill should be used when the user says "fix CVEs", "patch vulnerabilities", "apply security patches", "resolve security advisories", "batch CVE fix", "patch dependencies", "fix security findings", "remediate CVEs", "apply CVE fixes", "batch fix vulnerabilities", "resolve
Open skill - /arn-code-batch-cve-scan
This skill should be used when the user says "scan for CVEs", "CVE scan", "check for vulnerabilities", "find vulnerabilities", "check security advisories", "dependabot triage", "dependabot scan", "scan dependencies for security issues", "audit dependencies", "vulnerability
Open skill - /arn-code-batch-implement
This skill should be used when the user says "batch implement", "implement all", "batch execution", "implement all features", "parallel implement", "implement in parallel", "arness batch implement", "arn-code-batch-implement", "run batch implementation", "implement everything",
Open skill - /arn-code-batch-merge
This skill should be used when the user says "batch merge", "merge batch", "arness batch merge", "arn-code-batch-merge", "merge all PRs", "merge batch PRs", "merge the batch", "merge implemented features", "batch merge PRs", "merge open PRs", "merge all feature PRs", "combine
Open skill

