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 agentmods add skills/appsvortex/arness/arn-code-batch-planningnpx skills add AppsVortex/arness --skill arn-code-batch-planninggit clone --depth 1 https://github.com/AppsVortex/arnessWhat 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 | $0.00201 | $0.07039 |
| Opus 5 | $0.00101 | $0.03520 |
| Sonnet 5 | $0.00040 | $0.01408 |
| Haiku 4.5 | $0.00020 | $0.00704 |
Grade A, and why
arn-code-batch-planning 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 2d 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 — 620 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arness Batch Planning
Plan multiple features in a single session with parallel pre-analysis and pipelined plan generation. Supports features from greenfield Feature Tracker (F-NNN), GitHub issues, Jira issues, or plain descriptions. Pre-analyzes all selected features in parallel using arn-code-batch-analyzer agents to generate draft specs, then guides the user through sequential review. Plans are generated in the background while the user reviews the next spec.
This skill is a sequencer. It MUST NOT duplicate sub-skill logic. All pipeline work is done by the invoked skills and agents (arn-code-batch-analyzer, arn-code-feature-spec, arn-code-feature-planner, arn-code-save-plan). Arness-code-batch-planning handles: source detection, feature selection, parallel pre-analysis orchestration, sequential spec review, pipelined plan generation, plan review, and chaining.
Pipeline position:
Sources:
arn-spark (greenfield) -> feature-backlog.md ─┐
GitHub issues ─────────────────────────────────┤
Jira issues ───────────────────────────────────┤
v
**arn-code-batch-planning**
|
+-- Step 2.5: scope assessment (score each feature → swift/standard/thorough)
+-- Step 2.6: generate SWIFT/STANDARD plans (auto, no review)
+-- Step 2.7: parallel arn-code-batch-analyzer (thorough only → draft specs)
+-- Step 3: per thorough feature: arn-code-feature-spec (resume from draft)
+-- Step 3.5: per thorough feature: plan review → save-plan
|
v
arn-code-batch-implement
Step 0: Ensure Configuration
Read ${CLAUDE_PLUGIN_ROOT}/skills/arn-code-ensure-config/references/step-0-fast-path.md and follow its instructions. This guarantees a user profile exists and ## Arness is configured with Arness Code fields before proceeding.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 620 lines · 201 tokens per session scan A ce6382210926
arn-code-batch-planning is a skill published in the GitHub repository AppsVortex/arness (33 stars, last pushed 1mo ago), licensed MIT. It adds 201 tokens to every session and 7,039 once invoked, about $0.0010 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 2026-08-30.
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