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/catlog22/claude-code-workflow/csv-wave-pipelinenpx skills add catlog22/Claude-Code-Workflow --skill csv-wave-pipelinegit clone --depth 1 https://github.com/catlog22/Claude-Code-WorkflowWrote 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/catlog22/claude-code-workflow/csv-wave-pipeline)<a href="https://agentmods.dev/skills/catlog22/claude-code-workflow/csv-wave-pipeline"><img src="https://agentmods.dev/badge/skills/catlog22/claude-code-workflow/csv-wave-pipeline.svg" alt="Measured on agentmods" 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 | $0.00044 | $0.09728 |
| Opus 5 | $0.00022 | $0.04864 |
| Sonnet 5 | $0.00009 | $0.01946 |
| Haiku 4.5 | $0.00004 | $0.00973 |
Grade A, and why
csv-wave-pipeline 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 yesterday.
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 — 961 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Mode
When --yes or -y: Auto-confirm task decomposition, skip interactive validation, use defaults.
CSV Wave Pipeline
Usage
$csv-wave-pipeline "Implement user authentication with OAuth, JWT, and 2FA"
$csv-wave-pipeline -c 4 "Refactor payment module with Stripe and PayPal"
$csv-wave-pipeline -y "Build notification system with email and SMS"
$csv-wave-pipeline --continue "auth-20260228"
Flags:
-y, --yes: Skip all confirmations (auto mode)-c, --concurrency N: Max concurrent agents within each wave (default: 4)--continue: Resume existing session
Overview
Wave-based batch execution using spawn_agents_on_csv with cross-wave context propagation. Tasks are grouped into dependency waves; each wave executes concurrently, and its results feed into the next wave.
Core workflow: Decompose → Compute Waves → Execute Wave-by-Wave → Aggregate
Phase 1: Requirement → CSV
├─ Parse requirement into subtasks (3-10 tasks)
├─ Identify dependencies (deps column)
├─ Compute dependency waves (topological sort → depth grouping)
├─ Generate tasks.csv with wave column
└─ User validates task breakdown (skip if -y)
Phase 2: Wave Execution Engine
├─ For each wave (1..N):
│ ├─ Build wave CSV (filter rows for this wave)
│ ├─ Inject previous wave findings into prev_context column
│ ├─ spawn_agents_on_csv(wave CSV)
│ ├─ Collect results, merge into master tasks.csv
│ └─ Check: any failed? → skip dependents or retry
└─ discoveries.ndjson shared across all waves (append-only)
Phase 3: Results Aggregation
├─ Export final results.csv
├─ Generate context.md with all findings
├─ Display summary: completed/failed/skipped per wave
└─ Offer: view results | retry failed | done
Context Propagation
Two context channels flow across waves:
- CSV findings (structured):
context_fromcolumn →prev_contextinjection — task-specific directed context - NDJSON discoveries (broadcast):
discoveries.ndjson— general exploration findings available to all
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.
- yesterday First seen · 961 lines · 44 tokens per session scan A e667e14f1466
csv-wave-pipeline is a skill published in the GitHub repository catlog22/Claude-Code-Workflow (2,133 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 9,728 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 2026-09-03.
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